Data Scientist Aws Activate

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DESCRIPTION
Job summaryThe AWS Activate Program provides startups the resources they need to grow successfully on AWS. We do this by understanding the uniqueness of each and every startup that applies for Activate, and then personalizing the resources we make available to them. Our resources include (but are not limited to) AWS service credits, Business Support credits, technical education and training, opportunities for business and technical mentorship from Amazonians and startup peers, and personalized growth benefits. The Activate Personalization Team is the brains behind the Activate system. This team is responsible for ingesting startup data from multiple internal and external services, aggregating it into a holistic startup profile, and creating and productionizing ML models. Our team is looking for an experienced Data Scientist (DS) with outstanding leadership skills and the proven ability to build and manage medium-scale modeling projects. The candidate will be an expert across multiple data science domains including data transformation, machine learning, and statistics. Key job responsibilities
Research cutting edge algorithms, develop new models, and design and run experiments to improve customer personalizationPartner with scientists, engineers and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customersCollaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data qualityManipulate/mine data from databases (Redshift, SQL Server, Oracle DW, and Salesforce)
BASIC QUALIFICATIONS
Master's degree in Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science, or a related quantitative field or equivalent experience2+ years of experience with data querying languages (e.g. SQL, Hadoop/Hive, Scala) and statistical/mathematical software (e.g. R, Matlab, Stata)2+ years working experience as a Data Scientist or related positions
PREFERRED QUALIFICATIONS
Experience in an operational environment developing, fast-prototyping, piloting and launching analytic productsExperience in writing academic-styled papers for presenting both the methodologies used and results for data science projectsExperience with AWS services (Redshift, S3, EC2, Lambda, SNS/SQS, RDS, Aurora)Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
• The pay range for this position is $136,000 - $207,500 (yr.); however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered.
*This information is provided per the Colorado Equal Pay Act, the Pay Transparency Regulation of Jersey City Municipal Code, the New York City Human Rights Law. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.


Data Scientist Ii Ai Data Team

DESCRIPTION
Job summaryThe AI Data Team in Amazon Web Services (AWS) is looking for a Data Scientist with a passion for developing innovative methods to maximize the power of natural language data. This position is an opportunity to apply your expertise in a challenging but supportive environment. The position may be remote, with a preference for Santa Clara, Seattle, or New York City. We work in distributed teams, and strengthen our connections by traveling approximately five days per quarter for in person meetingsThe mission of the AI Data Team is to engineer the datasets critical to the success of AWS’s machine learning services. From chatbots to subtitles to search results and beyond, these products support dozens of languages and impact millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with the science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity.As a Data Scientist, you will start by learning the full context of critical projects for Lex, a conversational AI service used for building chatbots, consulting with stakeholders in science, engineering, and product teams. You will determine the appropriate metrics for data analysis and quality checks on data annotations, to ensure that the data is optimized for developing models that exceed customer expectations. You will consider domain gaps, data bias, and data noise in your analysis. You will design and write Python packages for these processes, and work with data engineering to implement them in data pipelines built to scale.You will also work with language engineers to understand the challenges we face in producing or acquiring data, and in generating high quality labels. You will stay up to date on developments in the field of data-centric AI, and experiment with new techniques for data cleaning, labeling, and augmentation. You will share your results in written documents and presentations to the data team and stakeholders. You will scale these methods for ongoing data collection and annotation, collaborating with data engineering as necessary.You will then contribute to large data team initiatives to design and build technical assets such as data warehousing and analytics tooling that support multiple programs. You will gain an understanding of data collection methods across the data team, and write code to provide metrics and insights across datasets that ensures the data is discoverable and reusable.Key job responsibilities* Design and write Python packages for analyzing natural language datasets, including domain gaps, data bias, and data noise* Develop innovative techniques for data cleaning, labeling, and augmentation, and scale these methods for ongoing data collection and annotation* Contribute to large initiatives for data warehousing and analytics tooling, writing code to provide metrics and insights across datasets that ensures the data is discoverable and reusable
BASIC QUALIFICATIONS
* Degree in a quantitative field such as computer science, mathematics, or computational linguistics* 3+ years hands on experience as a data scientist in an industry setting, including statistical modeling and data visualization* Proficiency in Python* Experience with natural language data and NLP techniques* Experience working with stakeholders such as product and engineering teams
PREFERRED QUALIFICATIONS
* Experience in developing and evaluating data annotation and data quality metrics* Experience using AWS tools and services* Strong written and verbal communication skills, with an ability to present complex technical information in a clear and concise manner to a variety of audiences* The pay range for this position is $136,000 - $207,500 (yr.); however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. *This information is provided per the Colorado Equal Pay Act, the Pay Transparency Regulation of Jersey City Municipal Code, the New York City Human Rights Law. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.


Lead Data Science Strategist

Overview
State Farm is hiring an exceptional Lead Data Science Strategist to drive out the Data Science Strategy, and direction for Big Data Analytics across our organization. Reporting directly to the Executive of Enterprise Technology, this role serves as a key member of the Leadership team and is regarded as the highest level of Data Science technical leadership.  The Lead Data Science Strategist is the key advisor on data science to all levels of leadership, consulting cross-functionally on broad, complex initiatives regarding big data, mathematics, statistics and technology. This role also develops best practices for analytics and data science, driving the development of a data driven enterprise with a common set of values, while also developing the State Farm brand in the public data science community through publications and other works that grow our value in the community.
Responsibilities
Consults and Informs for the overall direction of data science at State Farm, leading complex, sensitive and challenging data science projects with long term impactsPossesses extensive subject matter resource expertise on data science techniques and methodologies to solve complex problemsRegularly consults with C-Suite leadership, advising on and expanding data science opportunitiesGenerates new data science opportunities within State FarmObserves problems, spots opportunities, and creates solutionsIs recognized as an expert in the external data science community, bringing new and cutting-edge data science techniques to State FarmContributes to the external Data Science community through open-source contributions, journal article publication, and creates new intellectual property for State FarmCoaches and Mentors Data Scientists and Technical Leads
Qualifications
10+ years of relevant industry work experience providing advanced analytics solutions across large, complex organizationCompleted Master degree (PhD preferable):  Data Science; Computer Science; Applied Mathematics, Statistics, Economics or related with a focus on Artificial Intelligence (AI) or Machine Learning (ML) preferredIn-depth experience gathering and interpreting business requirements to design and create scalable data science solutions within a regulatory environment, ideally within insurance, healthcare, or financial services business vertical.  Extensive subject matter resource expertise on data science techniques and methodologies and is recognized as an expert both inside State Farm and in the external data science communityExperience working within the AWS ecosystem & deploying apps in a cloud native environment (docker, Kubernetes, Sagemaker, Databricks, etc.)Broad experience building different types of advanced analytic solutions, including some of the following: time series analysis, cluster analysis, tree-based algorithms, generalized linear models, or neural networks.Expert in data analysis using Python or RAbility to communicate complex information to varying levels of leadership, to include C-suite executives in straight-forward, non-technical language.  For Los Angeles candidates: Pursuant to the Los Angeles Fair Chance Initiative for Hiring, we will consider for employment qualified applicants with criminal histories.For San Francisco candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.For Colorado candidates:  Salary band $128,875.00-212,650.00
What You Can Expect:
Next Steps:  Competitive candidates may be invited to participate in the interview process. This includes a conversation with a recruiter, on demand video interview and hiring manager interviews.
*** Applicants are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g. H-1B visa) for this opportunity***
We are not just offering a job but a meaningful career! Come join our passionate team!
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Data Scientist

OverviewQualificationsJob DescriptionBenefits

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Employee Stock Purchase Program


Data Scientist Supply Chain Rpa


Senior Data Scientist Monzo Flex

We're looking for a Product Data Scientist excited to help us revolutionise the way people manage their finances. A key part of this role is product development our recently launched Monzo Flex, a product that gives customers a better way to pay later. You’ll help us understand and improve the user experience for a new product, help drive growth (we have over five million current account customers), and how we consider cross product dynamics across the range of borrowing products.
At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over five million customers in the UK. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.
Our Product Analytics team's mission is to Enable Monzo to Make Better Decisions, Faster
We have a strong culture of data-driven decision making across the whole company - and want to embed this into Monzo Flex, using powerful, real-time analytics to drive how we think about product development, growth hacking, and ongoing customer engagement.
As part of your role, you'll:

Work within a Product squad within the Borrowing Collective, collaborating closely with designers, PMs, and engineers to develop the testing and product roadmap for Monzo Flex.
Actively explore uptake and engagement of Monzo Flex and our other borrowing products, to make sure we can offer the right product and features to our customers
Be the expert on running simple and more complex experiments so that we can reliably measure the impact of changes we make to our borrowing products
Scale your knowledge and impact across data in borrowing by sharing your knowledge and working with others on projects and experiments
Find enjoyment in contributing to data across Monzo by sharing your insights, contributing to our core data pipelines and proactively spotting opportunities for applications of your work in other areas of the business

What’s special about data at Monzo?
Autonomy. We believe that people reach their full potential when you can remove all the operational obstacles out of their way and let them run with their ideas. This comes together with a strong sense of ownership for your projects. At Monzo, you will get full access to our data and analytics infrastructure. When you discover something interesting, there is nothing stopping you from exploring and implementing your coolest ideas.
Cutting-edge managed infrastructure. All our data infrastructure lives on the Google Cloud Platform, so you don't need to spend your time configuring or managing clusters, databases, etc. All of our infrastructure is designed so that we can have really high data quality, and spend most of our time using that data to support business decisions.
Automation. We aim to automate as much as we can, so that every person in the team can focus on the things that humans do best. As with all data science work, there’s some analysis and reporting, and as much as possible we encourage self-serve access to our data through Looker.
You should apply if:

What we’re doing here at Monzo excites you!

You're impact driven and eager to have a real positive impact on the company, product, users and very importantly your colleagues as well

You're commercially minded and can put numbers into business perspective

You’re as comfortable getting hands-on as taking a step back and thinking strategically

You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so

You're a team player whom your colleagues can rely on

You have solid grounding in SQL and preferably Python

You have experience in conducting large scale A/B experiments

Nice to haves:

You have multiple years of experience in product or growth analytics, preferably in a fast moving tech company

You have experience working in financial services

Logistics

We can help you relocate to London & we can sponsor visas.
This role can be based in our London office or remotely within the UK
We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical written exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions - you can get a feel for our hiring processes here.

#LI-NB1


Senior Data Scientist Marketing

We're looking for a Marketing Data Scientist excited to help us build the bank of the future. You'll work across all our marketing channels, to help Monzo understand the ROI across our entire marketing investment, from first to last £ spent. You'll have the opportunity to help supercharge our user growth, help grow our most exciting new products and be the voice of data for our marketing department.
At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over four and half million customers in the UK, with over 100,000 new people joining every month. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.
Our Marketing and Product Analytics team's mission is to
Enable Monzo to Make Better Decisions, Faster
We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
We work in cross-functional squads where you'll be a member of our central data discipline and fully embedded within our marketing department.
As part of your role, you'll:

Apply your expertise in quantitative analysis, data mining, performance marketing, and data presentation to find ways we can spend our marketing budget more effectively.
Own the measurement strategy for campaigns via methods such as randomised lift tests, geo-targeted lift tests, and marketing mix models
Work across our full product range and help shape our marketing investment strategy
Partner with our in-house and agency marketers to determine which channels are most effective
Manage relationships with our advertising partners and their analytics measurement teams, to collaborate on best practice and experimental design
Work with Engineers in our Marketing Tech team to define measurement requirements and guide their implementation
Use our cloud native data infrastructure (i.e BigQuery, Looker) to help us build visibility on channel performance
Stay up to date with the latest performance marketing measurement strategies in industry

You should apply if:

What we’re doing here at Monzo excites you!
You’re passionate about marketing science and understand the causal impact marketing can have

You're impact driven and eager to have a real positive impact on the company, product, users and very importantly your colleagues as well

You’re as comfortable getting hands-on as taking a step back and thinking strategically

You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so

You have multiple years of experience working in marketing or performance marketing analytics, preferably in a fast moving tech company

You have experience in conducting large scale A/B experiments, regional experimentation and marketing mix modeling

You have a solid grounding in SQL and preferably Python

Logistics

We can help you relocate to London & we can sponsor visas.
This role can be based in our London office or remotely within the UK
We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical written exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions - you can get a feel for our hiring processes here.

____________________________________________________________________________________________________________________________#LI-NB1


Senior Data Scientist

We're looking for a Senior Product Data Scientist excited to help build the bank of the future. You'll have the opportunity to super charge our user engagement in 2021 and help us to build a bank that customers truly love.
At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over four and half million customers in the UK, with over 100,000 new people joining every month. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.
Our Product Analytics team's mission is to

Enable Monzo to Make Better Decisions, Faster

We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
We work in cross-functional squads where every data scientist is a member of a central data discipline and fully embedded into 1 product squad alongside engineers, designers, marketers, product managers etc.
As part of your role, you'll:

Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with our products and how those insights can inform our product strategy
Guide and enable product teams to measure things that matter; initiate or help run A/B experiments to keep improving everything we do
Drive together with the finance team a unified company-wide understanding of the lifetime value of our users and how different product features are impacting user profitability
Liaise with engineers to keep making sure we collect the right data to produce relevant business insights

What’s special about data at Monzo?
Autonomy. We believe that people reach their full potential when you can remove all the operational obstacles out of their way and let them run with their ideas. This comes together with a strong sense of ownership for your projects. At Monzo, you will get full access to our data and analytics infrastructure. When you discover something interesting, there is nothing stopping you from exploring and implementing your coolest ideas.
Cutting-edge managed infrastructure. All our data infrastructure lives on the Google Cloud Platform, so you don't need to spend your time configuring or managing clusters, databases, etc. All of our infrastructure is designed so that we can have really high data quality, and spend most of our time using that data to support business decisions.
Automation. We aim to automate as much as we can, so that every person in the team can focus on the things that humans do best. As with all data science work, there’s some analysis and reporting, and as much as possible we encourage self-serve access to our data through Looker.
You should apply if:

What we’re doing here at Monzo excites you!
You're impact driven and eager to have a real positive impact on the company, product, users and very importantly your colleagues as well
You're commercially minded and can put numbers into business perspective
You’re as comfortable getting hands-on as taking a step back and thinking strategically

You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so
You're a team player whom your colleagues can rely on
You have solid grounding in SQL and preferably Python
You have experience in conducting large scale A/B experiments

Nice to haves:

You have experience in product or growth analytics, preferably in a fast moving tech company

Logistics

We can help you relocate to London & we can sponsor visas.
This role can be based in our London office or remotely within the UK
We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical written exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions - you can get a feel for our hiring processes here.

____________________________________________________________________________________________________________________________
#LI-NB2


Data Science Manager Operations

We're looking for Data Science Managers to help our product teams build the bank of the future. You’ll have the opportunity to lead a team of Data Scientists across our Operations collective.
As we continue to scale, we’re looking for an Operations Data science to lead our customer operations.
As a Data science manager, you’ll be working in an ever changing environment where we are building and iterating on our workforce processes and systems to ensure we keep delighting our customers. Your team will focus on how to optimise costs by improving our forecast and planning capabilities and supporting decisions on how to improve our service and systems.
We’re still growing, and this is the right time to review our tools, processes and operational footprint. You’ll help us build and improve these for now and for our future roadmap. We’re looking for a hands-on, data driven operational leader who can bring fresh thinking and new ways to inspire the team to deliver service excellence.
You’ll work closely with product managers, engineers, designers and researchers in an agile product environment. You’ll champion the use of data, bring ideas to life through rigorous experimentation and A/B testing. You’ll help us get the most out of volumes of cloud native data platform, spotting opportunities to make each area of our product work even better for our users. You’ll help your team grow, hiring new team members, supporting their personal development. Your team will drive product innovation and you’ll get to see the impact of all your work in the product changes we make.
We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.
We work in cross-functional squads where every data scientist is a member of a central data discipline and fully embedded into a product squad alongside engineers, product managers, machine learning engineers etc.
As part of your role, you'll:

Be a key leader in building a discipline of exceptional data scientists working on making Monzo world class at tackling operations problems
Assure that our forecasts are accurate and flexible
Help hire, develop and retain talented Data Scientists
Generate insights that can change the direction of product development
Establish yourself as a trusted partner to the product leadership teams with the capacity for getting things done, be it either hands-on or by leading others
Bring data leadership and rigour to our approach to product development in the operations function and build a strategic understanding of the business while structuring complex projects to bring them to life
Liaise with engineers to keep making sure we collect the right data to produce relevant business insights

What’s special about data at Monzo?
Autonomy. We believe that people reach their full potential when you can remove all the operational obstacles out of their way and let them run with their ideas. This comes together with a strong sense of ownership for your projects. At Monzo, you will get full access to our data and analytics infrastructure. When you discover something interesting, there is nothing stopping you from exploring and implementing your coolest ideas.
Cutting-edge managed infrastructure. All our data infrastructure lives on the Google Cloud Platform, so you don't need to spend your time configuring or managing clusters, databases, etc. All of our infrastructure is designed so that we can have really high data quality, and spend most of our time using that data to support business decisions.
Automation. We aim to automate as much as we can, so that every person in the team can focus on the things that humans do best. As with all data science work, there’s some analysis and reporting, and as much as possible we encourage self-serve access to our data through Looker.
You should apply if:

What we’re doing here at Monzo excites you!
You have multiple years of experience as a Data Science Manager, working as a Lead data scientist or Data Scientist
Experience in forecasting or operational research is a plus
You know what it takes to manage top tier Data Science talent
You’re excited by the opportunity to work autonomously to impact the future of a fast growing, ever evolving business
You consider yourself an empathetic leader and have experience managing data scientists and you really enjoy that part of the job
You have experience working together and collaborating with senior business stakeholders and product teams
You're familiar with using a variety of Data Science tools (from business intelligence, experimentation and causal inference through to machine learning), and coding languages (Python and SQL). You know when to pick the right tool, and can help others do the same

Logistics

We can help you relocate to London & we can sponsor visas.
This role can be based in our London office or remotely within the UK
We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions.

Equal Opportunity Statement
At Monzo, embracing diversity in all of its forms and fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone.
We're an equal opportunity employer. All applicants will be considered for employment without attention to ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity status or disability status.
What is Monzo about?
We’re a bank on a mission to make money work for everyone. By focusing on solving real problems rather than selling financial products, treating people fairly and being totally transparent, we believe we can make banking better.
Monzo started in 2015 with big plans and a little office in Shoreditch, London. Now we’re a fully-licensed bank with millions of customers in the UK, and well over a thousand employees around the world.
_________________________________________________________________________________________________________________________#LI-NJ1 #LI-Remote


Data Science Manager Financial Crime

We're excited to be looking for a Financial Crime Data Science Manager to help build the bank of the future. You'll have the opportunity to lead a part of the Financial Crime Data Science team and play a critical role in Monzo’s mission to make money work for everyone.
As a Data science manager, you’ll be working in an ever changing environment where we are building and iterating on our financial crime defence capabilities to ensure we keep Monzo and our customers safe. As a financial crime team we have a large impact on Monzo’s bottom line as fraud and scams are usually some of the biggest cost line items in a bank's P&L. In addition, we have a great influence on the overall customer experience and how protected they are. Most of the work we do results in directly measurable customer or company benefit which is incredibly satisfying.
Our Data Science Managers don’t have a permanent assignment to a problem space and might rotate into different financial crime areas after some time. The major problem spaces that we are working in are: fraud prevention, transaction monitoring for different types of suspicious activity, customer risk assessment and operational tooling to name the biggest ones. At the moment we are about 21 people in financial crime data, including 3 other Data Science managers who will be your peers.
As part of your job you’ll work closely with product managers, engineers, designers and researchers in an agile product environment. You’ll champion the use of data, bring ideas to life through rigorous experimentation and A/B testing. You’ll help us get the most out of large volumes of data stored on a modern cloud native data platform and with spotting opportunities to make each area of financial crime work even better for our users and for Monzo. As a people manager, you’ll help your team grow, hiring new team members, supporting their personal development. Your team will drive product innovation and you’ll get to see the impact of all your work in the product changes we make.
The role
As part of this role you'll:

Be a key leader in building a discipline of exceptional data scientists working on making Monzo world class at tackling financial crime
Establish yourself as a trusted partner to the financial crime and product leadership teams with the capacity for getting things done, be it either hands-on or by leading others
Bring data leadership and rigour to our financial crime function and build a strategic understanding of the business while structuring complex projects to bring them to life
Set the data strategy for financial crime area - from working with engineers on ensuring that we capture the right data to building predictive models that help us detect financial crime
Have the opportunity to manage exceptional Data Scientists and help their career progression and development
Be able to work on all aspects of financial crime as we operate as one team

You should apply if:

You have multiple years of experience in data, working as a lead Analyst or Data Scientist
You consider yourself an empathetic leader and have experience managing multiple data scientists and you really enjoy that part of the job
You’re as comfortable getting hands-on as well as taking a step back and thinking strategically and proactively identifying opportunities
You have experience working together and collaborating with senior business stakeholders and product teams

You're familiar with using a variety of Data Science tools (from business intelligence, experimentation and causal inference through to machine learning), and coding languages (Python and SQL). You know when to pick the right tool, and can help others do the same

You are passionate about reducing financial crime with data driven strategies

Nice to haves:

Experience from working with financial crime and regulated institutions

Logistics

We can help you relocate to London & we can sponsor visas.
This role can be based in our London office or remotely within the UK
We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.
Diversity and inclusion is a priority for us – if we want to solve problems for people around the world, our team has to represent our customers. So we need to attract the best talent and create an environment that supports and includes them. You can read more about diversity and inclusion on our blog.
If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.
The application process consists of a 30 min phone call with a recruiter, an initial call with someone from the team, followed by a practical exercise and 2-3 video interviews. We promise not to ask you any brain teasers or trick questions

Equal Opportunity Statement
At Monzo, embracing diversity in all of its forms and fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone.
We're an equal opportunity employer. All applicants will be considered for employment without attention to ethnicity, religion, sexual orientation, gender identity, family or parental status, national origin, veteran, neurodiversity status or disability status.
What is Monzo about?
We’re a bank on a mission to make money work for everyone. By focusing on solving real problems rather than selling financial products, treating people fairly and being totally transparent, we believe we can make banking better.
Monzo started in 2015 with big plans and a little office in Shoreditch, London. Now we’re a fully-licensed bank with millions of customers in the UK, and well over a thousand employees around the world.
_________________________________________________________________________________________________________________________#LI-NJ1 #LI-Remote


Sr Actuarial Analyst

The Role.
Root's approach to data and technology has opened the door to new ways of auto pricing: new data everywhere, new analytical approaches, and the massive computational power to finally put the two together. We're looking for actuaries that are ready to roll up their sleeves and get their hands dirty, building better processes and analytics from the ground up.
We're looking for a Senior Actuarial Analyst to execute and enhance our rate revision process and pricing analyses by developing and communicating key insights to drive effective decisions.  There's no playbook on how to do this; you'll be partnering within and between teams to creatively problem solve and incorporate insights into a final product.
What you'll be doing.
Execute pricing initiatives including state implementations and rate changes for auto and renters products
Support rate filings and engineering implementations
Leverage statistical and projection models to develop rating plans and recommendations for pricing improvements (example: rate indications, limit studies, state specific analysis etc)
Evaluate and analyze market data to facilitate competitive strategic decisions
Opportunities for growth with company into management or other more senior roles
What we're looking for.
3+ years of P&C insurance experience in an actuarial role
Demonstrable experience with analysis in R, Python or other programming language
Demonstrable experience in SQL or other database software


Actuarial Analyst

Root's approach to data and technology has opened the door to new ways of auto pricing: new data everywhere, new analytical approaches, and the massive computational power to finally put the two together. We're looking for actuaries that are ready to roll up their sleeves and get their hands dirty, building better processes and analytics from the ground up.
The position.
We're looking for aActuarial Analyst to execute and enhance our rate revision process and pricing analyses by developing and communicating key insights to drive effective decisions.  There's no playbook on how to do this; you'll be partnering within and between teams to creatively problem solve and incorporate insights into a final product.
What you'll be doing.
Execute pricing initiatives including state implementations and rate changes for auto and renters products
Support rate filings and engineering implementations
Leverage statistical and projection models to develop rating plans and recommendations for pricing improvements (example: rate indications, limit studies, state specific analysis etc)
Evaluate and analyze market data to facilitate competitive strategic decisions
Opportunities for growth with company into management or other more senior roles
What you should have.
1+ years of P&C insurance experience in an actuarial role
Demonstrable experience with analysis in R, Python or other programming language
Demonstrable experience in SQL or other database software


Data Scientist

About the Data Science Team
We're looking for data scientists with deep expertise in machine learning, optimization,  building data products, and/or statistics. As part of a small product team you will have full ownership over your domain, so you should be a person who dreams big, then executes well.
At Thumbtack, the Data Science team is responsible for a wide variety of problems spanning machine learning, statistics, and computer science:

Characterize marketplace dynamics. Thumbtack’s marketplaces consist of thousands of active markets across our service categories and U.S. cities. Via exploratory data analysis and experimental design, our team works to understand trends and behaviors within these markets.

Improve customer and service provider matching. Matching and optimization algorithms are fundamental to Thumbtack’s product: we now service millions of matches per week. Identifying better matches between customers and service providers has an incredible impact on the experience of customers and professionals transacting on our platform.

Model complex relationships in the presence of many confounding factors. Predictive modeling problems are everywhere across our product. Our team works to scope, design and implement machine learning models to support Thumbtack’s product.

Challenge
Our team is at the forefront of a massive amount of user data. We need to think a lot about both scaling as well as how to provide experiences for a wide set of users that we don’t necessarily know a ton about immediately. We are building experiences into our apps to onboard, engage, and re-engage our users and are constantly experimenting to produce delightful and consistent user experiences.
Responsibilities

Design and execute experiments, collect and analyze data to characterize our product
Architect and deploy machine learning systems to production
Design and implement metrics that align with company goals
Analyze a wide variety of data: structured and unstructured, observational and experimental
Collaborate with engineering, marketing, and economists to use sound statistical practices.

Must-Have Qualifications
If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone excited to join the team.

2 plus years of industry experience, M.S. or equivalent experience in Computer Science, Economics, Engineering, Math, Statistics, or other relevant technical field
Expert knowledge of machine learning techniques: regression and classification, clustering, neural networks, boosted decision trees, etc.
Ability to effectively read, write, and debug code in programming languages such as Python
Good knowledge of probability and statistics, including experimental design, optimization, and causal inference
Excellent written and verbal technical communication skills

Nice-to-Have Qualifications

Ph.D. in Computer Science, Economics, Engineering, Math, or Statistics
Expert knowledge of probability and statistics, including experimental design, predictive modeling, optimization, and causal inference
Experience with large-scale distributed systems

Thumbtack is a virtual-first company, meaning you can live and work from any one of our approved locations across the United States, Ontario or the Philippines. When it is safe to gather, we will begin to host in-person events on a regular basis. Remote employees will be expected to travel occasionally for these events to a Thumbtack library or offsite team-building location. In cities with 5+ employees, we are establishing local communities, where employees can gather for local events. Additionally, employees in the San Francisco, Salt Lake City, Toronto and Manila areas will have opt-in access to communal workspace at one of our Thumbtack libraries. We always prioritize the health and safety of our employees. Currently, participation in these events and Thumbtack library use are optional. Both require employees to be fully vaccinated.
#LI-Remote


Data Scientist

Who We Are

Arkestro is the leading Predictive Procurement Orchestration platform. Built to amplify the impact of procurement’s influence, Arkestro helps enterprises deliver a 2-5x lift on cost savings attributed to everyday purchasing and sourcing cycles. Top enterprises leverage Arkestro’s behavioral science, game theory and machine learning to predict and win faster value across every category of addressable spend.

Arkestro is scaling the first ever predictive procurement automation software. Typical enterprise procurement has many disparate data sources that are often underutilized to make smarter and more efficient purchases. Via a blend of predictive AI models and user-centric design, Arkestro is re-imagining enterprise procurement teams as a powerful lever to digitize and improve global supply chains. We’re looking for a passionate Technical Business Analyst to join our Product Team to help us achieve our vision of procurement that changes the world of business operations in positive and meaningful ways. Arkestro is at an exciting stage of growth, and this role will help build out the Data Team. The right candidate will have the opportunity to work with innovative customers and fantastic internal engineering and customer success teams to transform enterprise procurement. Given the early stage of Arkestro, this role has the ability to grow into several different areas of Data Team responsibility whether it is more technical or more customer-facing.

Tools and Technologies We Use

Data science and visualization: Dataiku, Verb, Python, SQL, Excel
Project management and collaboration: Asana, Miro, Pivotal Tracker, Slack
Workflow and Analytics: Intercom, Amplitude, Fullstory, Segment

An Ideal Candidate Has

Excellent communications skills, the ability to learn on the fly, and a desire for ownership
Advanced degree in CS, Math, Economics, Physics, Engineering, etc.
5+ years of experience translating real world data into clearly actionable insights
3+ years of experience building, deploying, and maintaining ML models
3+ years of experience with Python
Bonus: Experience with a data science studio tool (Dataiku, Databricks, Alteryx, etc.)

Day to Day Responsibilities

Ingest, transform, and explore customer data for use in visualizations and models
Automate model training, testing and deployment to API server (Dataiku)
Work closely with engineering to fit model to Arkestro web application requirements
Project manage data model lifecycle and performance with key stakeholders

Benefits

 •  Competitive salary and startup equity

 •  We are a remote-first team, but we like to get together for team building, design sprints, and customer visits

 •  We also have offices located in both Atlanta and San Francisco

 •  We are highly supportive of flexible work hours

 •  Unlimited PTO

 •  Generous 401k matching and healthcare, dental, and vision plans

 •  Every employee is given an annual budget of $1,000 for annual learning and development (i.e. books,

	 conferences, courses)

 •  Full-time employees are also given an initial $1,000 budget for home office supplies

Disclaimer

Please note this job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described and that additional tasks may be assigned to the employee from time to time; or the scope of the job may change as necessitated by business demands. Arkestro reserves the right to change duties, responsibilities and activities at any time with or without notice. Arkestro is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.


Senior Machine Learning Scientist

Stuart (DPD Group) is a sustainable 🌱 last-mile logistics company that connects retailers and e-merchants to a fleet of geolocalised couriers across several countries in Europe.

Our Mission 🚀
We are an impact-driven company that aims to build the future of logistics for a more sustainable world: shared, efficient and reliable. We are committed to creating a new standard for urban deliveries that meet today’s environmental and social challenges while offering a premium delivery experience blending speed, flexibility and convenience.

Our motto: “Make every delivery a moment all of us can truly celebrate!” More than 3000+ leading brands already partner with us across Restaurants, Grocery, Retail & Luxury, eCommerce and Professional Services to deliver all types of goods at the tap of a button. Stuart is a highly diverse and inclusive company of 700+ employees with 90+ nationalities working across France 🇫🇷, Italy 🇮🇹, Poland 🇵🇱, Portugal 🇵🇹, Spain 🇪🇸 and the U.K. 🇬🇧

It’s the right moment and the right place for us to make an impact on millions of people, as home delivery services hit a record high. And guess what? You can help us fulfil our vision 🙌

About the Data Science Team 🌟

The Data team's mission is to develop best-in-class algorithms for last-mile logistics and to enable everyone at Stuart to make data-driven decisions. The Data Science teams powers products and decisions with algorithms.
You will join our Data Science team to develop algorithm-driven solutions for core machine learning products of the platform that run in real-time at scale.

What will I be doing? 🤔

Participate in scientific discussions about our algorithms and provide original insights.
Formulate hypotheses about the problem at hand.
Build machine-learning models with a clear business impact and best software engineering practices.
Put your models in production alongside our dedicated team of backend and data engineers in short development cycles.
Monitor your models alongside our dedicated product analysts.

If you are passionate about high-performance machine-learning algorithms for complex problems, big data technologies, and mathematical modelling of business problems, we can guarantee you are in for a ride.

What do we need from you? 😎

4+ years of experience as a Data Scientist or any similar role (at least three years in non-academic positions).
Expertise in Python is mandatory. Good knowledge of a statically-typed language such as Java, Scala, or C++ is a plus.
Good software engineering skills to work seamlessly alongside our software engineers.
Experience equivalent to a Ph.D. or MSc in quantitative Sciences (Mathematics, Physics, Computer Science, Biology).
Good theoretical and practical knowledge of machine learning, especially in designing deep learning architectures.
Demonstrable experience in putting machine learning models into production.

Nice to have ✨

Experience in Apache Kafka or similar technology.
Familiarity in the design of event-driven architectures.
Some knowledge in related areas such as Operation Research and/or  Reinforcement Learning will be highly valued.

The stuff you wanna know 😉

Family-friendly work-life balance - work from home and flexible hours 🏡
Ticket Restaurant by Edenred (€11 ) 🥗
This is a remote work opportunity
Unlimited access to Udemy for all your learning and development needs 📚

Stuart Academy with regular workshops, Stu-Classes, and Stu-Talks 🎓
Stuart is putting Mental Health Awareness first! Wellness Allowance (€40 monthly) to use in any gym or sport class 🧘

Private healthcare provided by Sanitas 🧑⚕
Free monthly public transportation pass for non-remote workers 🚇
Work in an international, dynamic and passionate environment with a company culture focused on learning and development 🎉

You’ve read all this way but you’re missing a skill or two? No problem, it’s our job to up-skill you to take your career to the next level. What we’re trying to say is, don’t be afraid to apply if you don’t tick all the boxes  💪

At Stuart, we believe that employees today want to evolve in collaborative, high-growth environments where they can demonstrate their abilities and thrive both professionally and personally. We are convinced that employees need to find alignment between their inner values and their company’s culture and mission to unlock their full potential. We work to create a culture of empowerment, continuous learning and growth where everyone can bring expertise, own projects and easily measure their impact 🙌

Stuart is proud to be an equal opportunity workplace dedicated to promoting diversity. We don’t discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status or disability status 💙

Please note: Our Talent Acquisition Team is international coming from across the world 🌍 We kindly ask you to please submit your CV and application in English so that it can be reviewed correctly (unless the job posting is in a language other than English). Thank you 🤗

Want to learn more about us? Visit https://stuart.com/about-us/


Data Scientist Online

Work Styles at Zoom
In most cases, you will have the opportunity to choose your preferred working location from the following options when you join Zoom: in-person, hybrid or remote. Visit this page for more information about Zoom's Workstyles.
About Us
Zoomies help people stay connected so they can get more done together. We set out to build the best video product for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars.
We’re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Here, you’ll work across teams to deliver impactful projects that are changing the way people communicate and enjoy opportunities to advance your career in a diverse, inclusive environment.
The Data Science team lies at the foundation of Zoom’s success. We are looking for a rock-star to join our team to help us solve for a wide range of analytics challenges in the areas of campaign marketing and eCommerce.
We are looking for highly motivated individuals who would be excited to partner with our stakeholders to develop data products & solutions that will impact hundreds of millions of our users across the world. Expert communication, problem-solving, and having an innovative spirit will be the keys to success in this role.
You'll be working cross-functionally with teams of Product Engineers, Product Managers, Data Engineers, Sales and Marketing Managers on some of the most critical projects in the company.
RESPONSIBILITIES:
Research customer cohorts and design A/B experiments for web optimizations & marketing campaigns by splitting users groups into test and control and sampling users in the best way to drive open/click rates and conversions
Generate and deliver compelling insights to leaders to inform strategic decisioning on new products/initiatives and optimizations to our website
Build automated dashboards featuring event/clickstream data to ensure the right insights are delivered to our Marketing teams
Work with stakeholders to scope and define the needs of business and manage data engineering projects to ensure accuracy and timely delivery
Build and maintain statistical models that deliver value to our partner teams
Lead and conduct deep-dive research and analysis to identify opportunities
REQUIREMENTS
Minimum 4+ years of experience using data to facilitate decisions OR
Advanced Degree (Masters or PhD in Computer Science, Data Science or other quantitative field) and 2+ years of experience using data to facilitate decisions
Minimum 1+ years of experience in Marketing / Customer analytics space
Minimum 2+ years of experience in SQL
Minimum 2+ years of experience with statistical analysis using Python or R
PREFERRED
1+ years of experience using Google Analytics
1+ years of experience using Tableau/Domo/Spotfire
Experience in Salesforce Marketing Cloud and Pardot are a plus
Minimum 2+ years of experience with tools like DataRobot/Data bricks/ SageMaker
Python/ R and SQL - at-least 2 years experience
Prior experience working in ecommerce, marketing, customer analytics space - at-least 1 year
Statistics and modeling experience -  1 year
Communication skills - ability to ask right questions, translate data to business insights and communicate technical information to business audience
Ability to work with ambiguity, strategic thinking and motivated learner
We believe that the unique contributions of all Zoomies is the driver of our success. To make sure that our products and culture continue to incorporate everyone's perspectives and experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Zoom is proud to be an equal opportunity workplace and is an affirmative action employer. All your information will be kept confidential according to EEO guidelines.
We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law. If you need any assistance or accommodations due to a medical condition, or if you need assistance accessing our website or completing the application process, please let us know by emailing us at careers@zoom.us.
Colorado Salary Range or On Target Earnings:
Minimum:
$97,920.00 USD
Maximum :
$181,170.00 USD
In addition to the base salary and/or OTE listed, Zoom has a Total Direct Compensation philosophy that takes into consideration base salary, bonus and equity value.  Information about Zoom’s benefits is here.  Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience.  We also have a location based compensation structure; there may be a different range for candidates in other locations.
Zoom requires all U.S. employees who will work in person at a Zoom office, attend in-person Zoom meetings or have in-person customer meetings to be fully vaccinated.  Zoom will consider requests for reasonable accommodations for religious or medical reasons as required under applicable law.
Explore Zoom:
Hear from our leadership team
Browse Awards and Employee Reviews on Comparably
Visit our Blog
Zoom with us!
Find us on social at the links below and on Instagram
View more jobs, sign up for job alerts and join our talent community. Visit the Zoom careers site.
#LI-Remote


Manager Data Scientist Apollo Team

Overview
11 West 19th Street (22008), United States of America, New York, New YorkManager, Data Scientist - Apollo Team  (Remote-Eligible)
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description:
Emerging Merchant Businesses is a new team dedicated to discovering and accelerating high-growth opportunities at Capital One.  Our newly formed organization is composed of incredibly exciting Capital One businesses, including Capital One Shopping, Flex Pay, and Apollo.  As part of the EMB team, you will  work alongside experts across customer experience, data, technology (and more!) who are moving quickly to find the next big business at the company.  We are looking for talented associates who are motivated to be part of this journey and help us shape the future of Capital One, growing and learning with a team who will invest in your development, foster an inclusive environment, and lead with heart to change banking for good.
As a Manager Data Scientist on the Apollo team in Emerging Merchant Businesses, you are a part of a team that develops the core technology which drives our industry-leading understanding of the U.S. business landscape, generating valuable business insight from many disparate sources. The Apollo team is building technology that allows us to acquire, understand, and make inferences on large, disparate business data sets. This requires ideas from across the machine learning skillset, applied to problems and data that are unique to our business.  You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.
Role Description
In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers loveLeverage a broad stack of technologies — Python, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual dataBuild machine learning models through all phases of development, from design through training, evaluation, validation, and implementationFlex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Capital One is open to hiring a Remote Employee for this opportunity.
Basic Qualifications:
Bachelor’s Degree plus 6 years of experience in data analytics, or Master’s Degree plus 4 years in data analytics, or PhD plus 1 year of experience in data analyticsAt least 2 years of experience in open source programming languages for large scale data analysisAt least 2 years of experience with machine learningAt least 2 years of experience with relational databases
Preferred Qualifications:
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analyticsAt least 1 year of experience working with AWSAt least 1 year of experience with version control, CI/CD, and containerization/deployment technologiesAt least 4 years experience in Python, Scala, or R for large scale data analysisAt least 4 years experience with machine learningAt least 4 years experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
No agencies please.  Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace.  Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


Data Scientist Machine Learning Ads Targeting

Location: Remote-Friendly
Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly and will continue to be after the pandemic.
We are looking for a Machine Learning Data Scientist to work within the Ads Targeting team. You will work closely with engineers and product managers to 1) develop algorithms and toolings to empower various ML focused Targeting products, 2) shape the product roadmap and strategy.
Responsibilities:

Build machine learning models to improve ML focussed Ads Targeting products such as User Lookalike Models, Keyword Targeting, User Interest Matching.
You will design metrics and mechanisms to understand and evaluate the performance of various Targeting products.
Be involved in all phases of modeling such as ideation, offline modeling, online implementation, experimentation, deploy and post-launch monitoring/measurements.
Serve as a thought-partner for product managers, engineering managers in shaping the Targeting roadmap and strategy by identifying opportunities through deep-dive analyses and/or modeling.
This role will have a lot of overlap with other Machine Learning Engineer roles, but will differ in a couple of areas. First is that you will work mainly on offline modeling and rely on engineers to productionize your models. Secondly, you will have a keen interest in the collection and quality of underlying data (experiment design and analysis, data deep dive), along with working on ETLs and data aggregations needed for training, testing and productionizing models.

Required Qualifications:

Experience in machine learning applications of natural language processing, recommendation system, large scale unsupervised learning.
Bachelor’s degree or above in Mathematics, Statistics, Machine Learning, Computer Science, Economics, or other quantitative fields
Master’s or PhD degree is preferred but not required
Strong analytical and communication skills
Strong skills in SQL and programming (Python or R)
Understanding of experimentation and causal inference analyses
Experience in online advertising is preferred but not required

Benefits:

Annual Personal & Professional development funds
401k matching plan
Flexible PTO
Paid holidays + Wellness days
Remote friendly


Senior Data Scientist

At Arena Analytics, we believe that talent is equally distributed, but opportunity is not. Our goal is to rewire the labor market by applying predictive analytics, data science, and artificial intelligence to transform the way organizations identify, match, and hire people. Through our solutions, employers maximize retention by hiring people more likely to stay, improve performance by matching people to the right jobs, and reduce bias in the hiring process by leveraging our powerful AI model. We’re looking for passionate, collaborative, entrepreneurial people who care about building valuable solutions to fundamentally shift hiring practices for the better.
Job Responsibilities
Reporting to the Director of Data Science, your main goal is to lead by example for the DS team while improving current predictive models, pushing prototyped models into production, and creating new models from a combination of external data, client data, and Arena generated data. We seek a dynamic senior data scientist who has a penchant for systems thinking, a collaborative spirit, and an inquisitive mind. As a Senior Data Scientist, you will play an active role in creating impact for our clients through our predictive modeling and be responsible for the quality of those models.
Responsibilities include but are not limited to:
Developing innovative solutions to business, product or technical requests using appropriate machine learning and analysis techniquesPrototype solutions using appropriate machine learning or statistical techniquesPlaying a pivotal role in implementing such solutions with the support of Data EngineeringReviewing existing processes, approaches, and models related to data science; propose and initiating solutions and/or improvementsDisseminating knowledge and techniques and solidifying best practices by contributing to internal tools, libraries, and documentationMentoring more junior data scientists Contributing code and documentation to the company code/knowledge base
Qualifications and Skills
Excellent Python skills (numpy, pandas, scikit-learn, etc.), familiar with open source libraries and tools for data science such as TensorFlowStrong SQL skills and ability to implement general best practices; familiarity with MLOps a strong plusSuperior communication and data visualization skills with demonstrated ability to complete data science roadmap projectsTrack record of developing and deploying machine learning models with diversity of model types Familiarity with agile development and comfortable implementing agile methodologies in partnership with cross-functional teamsComfortable writing reproducible, well-commented code and participating in code reviewsExperience with a few of the following: classification models, forecasting, neural networks (GANs especially), experimental design and A/B testing, or recommender systemsExperience with sophisticated statistical or econometric models
Education and Experience Requirements
Extensive experience with machine learning and practical experience in a ‘data as a product’ organization implementing predictive modeling5+ years of practical experience as a data scientist in a product-driven organization working with data and predictive modeling OR an advanced degree in a quantitative field (such as computer science, statistics, a quantitative social, biological, or physical science) with 2+ years of work experience that involved significant project management and predictive modeling 4+ years of experience working in a position that requires critical thinking, writing for internal and external communications, and familiarity with common tools like Google Workspace (Docs, Sheets, etc.)/Microsoft Office/etc. or a Bachelor’s degreePrior experience at a growing SaaS business is a strong plus
Work Hours and Benefits
Arena Analytics is a remote friendly company, with a main office in Baltimore, MD for those who love an office environment, and the opportunity to work remotely in multiple states. We believe in work-life balance and want our full-time exempt employees to complete their work within a 40 hour work week. We offer a competitive salary and benefits, equity grant, 401K, PTO, and annual learning stipend.
EEO Statement
Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.


Data Scientist I Forecasting

Purpose of Job
About USAAUSAA knows what it means to serve. We facilitate the financial security of millions of U.S. military members and their families. This singular mission requires a dedication to innovative thinking at every level.
Job Description SummaryDevelop and analyze data to predict business results or member behavior. Experienced knowledge in statistics, mathematics, and tools used in predictive modeling. Partner cross-functionally with business to deliver breakthrough analytical solutions to support a winning strategy in a constantly evolving business environment.
This position is a Hybrid position if within a commutable distance in San Antonio, TX, and Charlotte, NC, offices. Remote Opportunity is available for those not located within a commutable distance.
Job Requirements
Identifies and manages existing and emerging risks that stem from business activities and the job role. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled. Follows written risk and compliance policies, standards, and procedures for business activities. Partners with other analysts across the organization to fully define business problems and research questions.Supports SME's on cross functional matrixed teams to solve highly complex work critical to the organization.Integrates and extracts relevant information from large amounts of both structured and unstructured data (internal and external) to enable analytical solutions.Conducts advanced analytics leveraging predictive modeling, machine learning, simulation, optimization, and other techniques to deliver insights or develop analytical solutions to achieve business objectives.Supports Subject Matter Experts (SME's) on efforts to develop scalable, efficient, automated solutions for large scale data analyses, model development, model validation and model implementation.Works with IT to research architecture for new products, services, and features.Develops algorithms and supporting code such that research efforts are based on the highest quality data.Translates complex analytical and technical concepts to non-technical employees to enable understanding and drive informed business decisions.
Minimum Requirements:
Master's degree in Computer Science, Applied Mathematics, Quantitative Economics, Statistics, or related field; OR 6 years of related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.4 years of related experience in predictive modeling, large data analysis and computer science.Proficient knowledge of the function/discipline and demonstrated application of knowledge, skills, and abilities towards work products.Proficient level of business acumen in the areas of the business operations, industry practices and emerging trends.Experience in data mining and statistical analysis.Knowledge of Data Science principals and experience with data science methodologies.Experience with any one of the following statistical and predictive modeling approaches: Gaussian Process; Markov Models; Hierarchical Clustering; K-Means; Linear Regression; Logistic Regression; Monte Carlo Simulation; Neural Networks.
Preferred Experience:
Advanced degree in Data Science, Financial Engineering, Statistics, Economics, Engineering, Mathematics, Actuarial Sciences, or related fieldExperience with the development of regulatory models within the banking industry (stress testing, IRR, ALM)Strong background in traditional statistical methods as well as machine learning algorithmsExperience working with account level data covering an extended periodComfortable using the capabilities of the Domino platform and developing models in various platforms/languages (Python, R, SAS, etc.)Experience with the model risk management process
The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.
Compensation:
USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market position. The salary range for this position is: $88,200 - $158,900.
Employees may be eligible for pay incentives based on overall corporate and individual performance or at the discretion of the USAA Board of Directors.
*Geographical Differential: Geographic pay differential is additional pay provided to eligible employees working in locations where market pay levels are above the national average.
Shift premium will be addressed on an individual basis for applicable roles that are consistently scheduled for non-core hours.
Benefits:
At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning, and continuing education assists employees with their professional goals.
To see details on our outstanding benefits, visit USAA Total Rewards.
Relocation assistance is not available for this position.


Decision Science Analyst Mid Level Data Management

Purpose of Job
We are seeking a talented Decision Science Analyst for either our San Antonio Home Office, Plano Campus, Phoenix Campus, Charlotte Campus, Colorado Springs Campus, Tampa Campus, or remote work environment available.
Provide decision support for business areas across the enterprise. Staff in this area will be responsible for applying mathematical and statistical techniques and/or innovative /quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer business objectives and drive change. The essence of work performed by the Decision Science Analyst involves gathering, manipulating and synthesizing data (e.g., attributes, transactions, behaviors, etc.), models and other relevant information to draw conclusions and make recommendations resulting in implementable strategies.
Job Requirements
About USAA
USAA knows what it means to serve. We facilitate the financial security of millions of U.S. military members and their families. This singular mission requires a dedication to innovative thinking at every level.
Primary Responsibilities:
Identifies and manages existing and emerging risks that stem from business activities and the job role.Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.Follows written risk and compliance policies, standards, and procedures for business activities.Leverages intermediate and some advanced business, analytical and technical knowledge to participate in discussions with cross functional teams to understand and collaborate on business objectives and influence solution strategies.Applies advanced analytical techniques to solve business problems that are typically medium to large scale with impact to current and/or future business strategy.Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer the business objective and drive the appropriate change. Translates recommendation into communication materials to effectively present to colleagues for peer review and mid to upper-level management.Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).Integrates/transforms disparate data sources and determines the appropriate data hygiene techniques to apply.Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.Understands and adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.Delivers analysis/findings in a manner that conveys understanding, influences mid to upper-level management, garners support for recommendations, drives business decisions, and influences business strategy.
When you apply for this position, you will be required to answer some initial questions.  This will take approximately 5 minutes.  Once you begin the questions you will not be able to finish them at a later time and you will not be able to change your responses.
Minimum Requirements:
Bachelor's degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline; OR 4 years of related experience in statistics, mathematics or quantitative analytics (in addition to the minimum years of experience required) may be substituted in lieu of degree.4 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance) OR Advanced degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline with 2 years experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance).Demonstrates competency in mathematical and statistical techniques and approaches used to drive fact-based decision-making.Intermediate and some advanced knowledge of data analysis tools, data visualization, developing analysis queries and procedures in SQL, SAS, BI tools or other analysis software, and relevant industry data & methods and ability to connect external insights to business problems.
Preferred Experience:
2+ years hands on development experience with Python in a professional setting for process automation and advanced analytical capabilities.2+ years hands on development experience with Tableau.2+ years hands on development experience and expert knowledge working with a variety of data platforms (Snowflake, Salesforce, Hadoop, Oracle) and tools / techniques (API, Virtualization) to extract and synthesize data into meaningful and actionable insights.Basic understanding of best practices and concepts for Data Management (Data Quality, Data Governance, Data Modeling, Data Architecture).
The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.
Compensation:
USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market position. The salary range for this position is: $72,900 - $131,400 *(this does not include geographic differential it may be applied based on your work location).
Employees may be eligible for pay incentives based on overall corporate and individual performance or at the discretion of the USAA Board of Directors.
*Geographical Differential: Geographic pay differential is additional pay provided to eligible employees working in locations where market pay levels are above the national average.
Shift premium: will be addressed on an individual-basis for applicable roles that are consistently scheduled for non-core hours.
Benefits:
At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness.  These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs.  Additionally, our career path planning and continuing education assists employees with their professional goals.
Please click on the link below for more details.
USAA Total Rewards
Relocation assistance is not available for this position.


Decision Science Analyst Lead Data Management

Purpose of Job
We are seeking a talented Decision Science Analyst Lead for either our San Antonio Home Office, Plano Campus, Phoenix Campus, Charlotte Campus, Colorado Springs Campus, Tampa Campus, or person may also work in a remote work environment is available.
Provide decision support for business areas across the enterprise. Staff in this area will be responsible for applying mathematical and statistical techniques and/or innovative /quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer business objectives and drive change. The essence of work performed by the Decision Science Analyst involves gathering, manipulating and synthesizing data (e.g., attributes, transactions, behaviors, etc.), models and other relevant information to draw conclusions and make recommendations resulting in implementable strategies.
Job Requirements
About USAA
USAA knows what it means to serve. We facilitate the financial security of millions of U.S. military members and their families. This singular mission requires a dedication to innovative thinking at every level.
Primary Responsibilities:
Identifies and manages existing and emerging risks that stem from business activities and the job role.Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled.Follows written risk and compliance policies, standards, and procedures for business activities.Leverages expert business, analytical and technical knowledge to lead discussions with cross functional teams to understand and collaborate highly complex business objectives and influence solution strategies.Applies advanced analytical techniques to solve business problems that are typically large scale with significant impact to current and/or future business strategy.Organizes and oversees the development of requirements/resources necessary to meet established objectivesApplies innovative and scientific/quantitative analytical approaches to draw conclusions and make recommendations to answer the business objective and drive the appropriate change. Translates recommendation into communication materials to effectively present to all levels of management.Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).Integrates/transforms disparate data sources and determines the appropriate data hygiene techniques to apply.Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.Monitors, understands and adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.Succinctly delivers complex analysis/findings in a manner that conveys understanding, influences senior executives, garners support for recommendations, drives business decisions, and influences business strategy.Provides subject matter expertise in operationalizing recommendations.Researches and pursues the latest and/or industry leading practices in data and analytics, (Ex: Cloud, Data Mining, Python, Neural Networks, Sensor data, IoT, Streaming/NRT data) to advance the overall DSA community knowledge.Identifies opportunities to continue to learn in the data and analytics space, whether informal (E.g., Coursera, Udemy, Kaggle, Code Up, etc) or formal (E.g. Certifications or advanced coursework).Innovates to create new and emerging data sets, and incorporation (data wrangling, data munging) into new insights
When you apply for this position, you will be required to answer some initial questions.  This will take approximately 5 minutes.  Once you begin the questions you will not be able to finish them at a later time and you will not be able to change your responses.
Minimum Requirements:
Bachelor's degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline is required; OR 4 years of related statistics, mathematics or quantitative analytics or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.8 years of data & analytics experience; OR 6 years of data & analytics experience and up to 2 years of progressive functional business relevant experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing etc.) for a total of 8 years combined experience; OR Advanced degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline and 6 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing, etc.).3 years of direct and/or indirect management experience.Demonstrates expert skills in mathematical and statistical techniques and approaches used to drive fact-based decision-making.Expert knowledge of data analysis tools, data visualization, developing analysis queries and procedures in SQL, SAS, BI tools or other analysis software, and relevant industry data & methods and ability to connect external insights to business problems.
Preferred Experience:
Strong technical acumen and demonstrated ability developing, implementing, and leading Data & Analytics strategies requiring oversight and partnership with cross-functional teams.Strong leadership presence and extensive experience partnering with and presenting to Executive leadership. Demonstrated ability to craft a message at the appropriate level, influence and gain support.4+ years hands on development experience with Python in a professional setting for process automation and advanced analytical capabilities.4+ years hands on development experience with Tableau or equivalent application for Business Intelligence.5+ years hands on development experience and expert knowledge working with a variety of data platforms (Snowflake, Salesforce, Hadoop, Oracle) and tools / techniques (API, Virtualization) to extract and synthesize data into meaningful and actionable insights.3+ years leadership experience training and mentoring junior level analyst to develop skillsets in data extraction, manipulation and analytical techniques and tools (SQL, Python, Tableau).Six-Sigma certification or equivalent experience in process engineering with a demonstrated ability operating within framework in the development of business strategies and the improvement / optimization of processes. Basic understanding of best practices and concepts for Data Management (Data Quality, Data Governance, Data Modeling, Data Architecture).
The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.
Compensation:
USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market position. The salary range for this position is: $106,800 - $192,300 *(this does not include geographic differential it may be applied based on your work location).
Employees may be eligible for pay incentives based on overall corporate and individual performance or at the discretion of the USAA Board of Directors.
*Geographical Differential: Geographic pay differential is additional pay provided to eligible employees working in locations where market pay levels are above the national average.
Shift premium: will be addressed on an individual-basis for applicable roles that are consistently scheduled for non-core hours.
Benefits:
At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness.  These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs.  Additionally, our career path planning and continuing education assists employees with their professional goals.
Please click on the link below for more details.
USAA Total Rewards
Relocation assistance is not available for this position.
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