nathansutton/data-science-job-descriptions huggingface dataset:
Senior Data Scientist at Bolt

The Data Platform team works closely with all teams and cross-functional partners (including product, engineering, and data analysts) to build a foundational data stack powering business analytics.
We are looking for someone to play a mission-critical role in designing and building the data mining algorithms, and data analytics pipelines at Bolt. We’re looking for someone with the experience, creativity, and passion for producing world-class technology who can support our product, leadership and marketing teams with insights gained from analyzing our data. Other teams at Bolt, other companies, and consumers alike will rely heavily on what you build, and you’ll have a ton of trust and responsibility. If challenges excite you, and you’re ready for a large one, let us know.
Check out our Engineering Blog!
Responsibilities

Build production ready data mining and big data analytics algorithms and pipelines; your models will be the engine that powers all online commerce through Bolt
Conduct data analysis to determine which policies we adopt and help inform strategic growth
Build statistical models, data pipelines, data mining, data analytics, and production ready services to serve offline and live traffic
Work with other teams at Bolt to engineer data models and extract data insights that help improve Bolt business

About you

Passion to improve e-commerce businesses
Strong communication skills in a cross-functional team
Unrelenting focus on impact
Ability to formulate business problems into quantitative objectives and developing methodological solutions

Requirements

MS/PhD in math, statistics, computer science, or other quantitative field
3+ years of experience in developing ML/statistical models in an applied setting
Knowledge of statistical concepts and techniques such as statistical inference, causal inference, or predictive modeling
Knowledge of data mining, and big data analytics techniques
Experience with big data processing pipelines and orchestration tools
Mastery in SQL or other big data processing languages
Experience with one of the programming languages such as Python, R, Java, Scala

Preferred

Experience with big data technologies such as BigQuery, Spark, Dataflow, Apache Beam, Pubsub, Cloud Functions, EMR, S3, Glue, Kinesis Firehose, Lambda,
Data Scientist Ii at Braze

Braze is seeking a Data Scientist to join our Growth team to automate and optimize our customers’ growth and retention programs through ML-assisted decision-making, and prediction. 
At Braze, we don’t just use machine learning to build models, we’ve built an on-demand ML model delivery platform to help our customers take advantage of the billions of users and hundreds of billions of data points that flow through our systems.
You will help discover the scope of what is possible with machine learning and AI in our systems, test and validate new predictive and statistical features, and tailor complex AI workflows for easy use by non-technical users. You will help build processes for maintenance and monitoring of these tools as well as for management and sharing of model code and testing.
WHAT YOU'LL DO

Collaborate with Engineering, Product, and Data Consultants to build innovative ways to leverage data and automate decision-making for our customers. 


Explore and analyze the billions of daily data points that Braze’s customers generate in search of predictive, valuable, actionable signals.
Build, analyze, and iterate on models that are best suited for the job, whether that’s supervised or unsupervised learning, neural networks, or simple regressions
Build processes to help catalog, maintain, and share the above with fellow data scientists and engineers

WHAT YOU HAVE

Masters in Computer Science, Applied Mathematics, or similar computational field or equivalent experience
Extensive experience prototyping, refining, and deploying predictive models and machine learning & AI, neural networks in a production setting
Fluent in Python
Experience with frameworks such as TensorFlow, PyTorch, or similar
2+ years of software engineering experience
Proficiency with relational databases 
2+ years working with cloud or distributed systems

Bonus:

Publication record in machine learning, artificial intelligence, or similar algorithmic fields
Familiarity with document-based databases
Senior Data Scientist at Cherre

Cherre is the leader in real estate data and insight. We connect decision makers to accurate property and market information, and help them make faster, smarter decisions. By providing a unique "single source of truth," Cherre empowers customers to evaluate opportunities and trends faster and more accurately, while saving millions of dollars in manual data collection and analytics costs.

Cherre is looking for a Senior Data Scientist who will be building ML algorithms and AI. This role requires a combination of quantitative and software engineering skills to build scaleable solutions. Because of the complexity  and variety of the data sets we use, it's critical that you have an interest in learning Real Estate and Derived datasets. Previous Real Estate experience is not required. You will not only do analysis, but will also be expected to deliver production code. 


We are remote-first company. This role is open for #BI-Remote or #Hybrid 


You Have

Proven record of delivering successful data science projects.
3+ years of industrial software engineering experience with an emphasis on data-centric technologies.
Advanced degree in a STEM field.
Practical knowledge of cloud computing ecosystems (AWS, Azure, Google Cloud).
Fluency in Python and SQL. Experience with PySpark is a plus.
Excellent communication skills, and an ability to explain your work to customers



Benefits

Competitive Base Salary
Equity
Range of Healthcare Plans
Paid Parental Leave
Educational Credit
Unlimited Vacation
Flexible Work Schedule





If this opportunity sounds interesting, apply or reach out to our internal talent team. We are happy to tell you more about Cherre: the technology we work with, the problems we solve, the team we are assembling, and the culture we all contribute to. We are excited you are considering working with us and look forward to hearing from you!

“At the top of the mountain we are all snow leopards.” - Hunter S. Thompson

Cherre is an equal opportunity employer. We pride ourselves on hiring the best people for the job no matter their race, sex, orientation, nationality, religion, disability, or age.
Senior Data Scientist Wind Resilience at One Concern

About One Concern

One Concern brings disaster science together with machine learning for better decision-making. We quantify resilience from catastrophic perils, empowering leaders to measure, mitigate, and transfer risk. We believe that by pioneering cutting-edge science, we can make disasters less disastrous and, ultimately, build planetary-scale resilience. 

The Role 


One Concern is growing rapidly, and we are looking for a passionate, mission-driven Senior Data Scientist, Wind Resilience to join our team. Help us develop a global-scale resilience prediction model against natural disasters, focused on wind resiliency. Apply technology and knowledge to enhance the resilience of the business, community, and people.


What You'll Do

Build a global-scale resilience model to predict the societal and economic impact and recovery of the built environment against disasters
Build and improve existing resilience prediction models
Work with and support domain experts and data scientists in different hazard products
Demonstrate up-to-date modeling skills (ML/statistical) and apply this to the development, execution, and improvement of action plans
Assess the potential usefulness and validity of new approaches and data sources.
Identify key problems in prediction models and propose innovative solutions.
Formulate your own problems as the problem might not always be defined for you
Collaborate with an interdisciplinary team of software engineers and data scientists on cross-functional projects, interpreting data, and translating into actionable insights



Qualifications and Experience


Ph. D.  or MS in structural engineering, civil engineering, mechanical engineering, or related field.

2+ year of industry experience in risk modeling/assessment
Strong background in statistics, probability theory, machine learning, and quantitative analytics (coursework or experiences)
Domain knowledge of wind resilience modeling
Experience in wind vulnerability model developments (machine-learning models or statistical models)
Hands-on experience in performing data analytics for a large set of data
Ability to work independently as well as in a team environment
Proficient in Python



Nice to Haves

Experience in infrastructure vulnerability assessment
Experience in the assessment of climate risks
Experience in community resilience modeling
Experience in large scale simulations
Experience in catastrophe risk modeling
Strong publication record


Compensation will be competitive with the market for this position and will include equity consideration. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, natural origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Data Scientist at Koho

About KOHO
KOHO is a quickly scaling FinTech company backed by leading investors and advisors from around the world. We started KOHO because we believe in doing two things:


Democratizing access to the best financial products and giving everyone a great financial foundation. 

Since our journey began 6 years ago, we’ve raised more than $340M, grown the KOHO Collective to over 250 employees, and created accounts for more than 600,000 Canadians.

About the Role

We’re building a world-class financial product and we need someone to help take our data operations to the next level. Our team is growing fast, and we’re looking for a Data Scientist to join us. You understand the data-driven decision making needs of a high-growth organization and are focused on concrete outcomes and KPIs. You look for the highest leverage solution to the most important problems, through either pragmatic analysis, a predictive model, or unsupervised learning methods.

Please Note: This is a remote position and is available to those who are legally entitled to work in Canada.


What You'll Do

You will design and develop statistical and data science models which will be used to improve the financial lives of many Canadians.
You will assist with model deployment and monitoring, as well as re-training or updating when necessary
You will coordinate and maintain communication with business stakeholders on data science-related projects
You will create dashboards or conduct ad-hoc analysis to answer pertinent or urgent data-related questions
You will document results, insights and methodology, as well as contribute to internal knowledge sharing within the Data team through talks and presentations.



Who You Are

You have 3+ years of experience working with data and engineering teams
You have expert knowledge of Python and SQL
You are passionate about applying data science in financial services, with ideas on how and where to improve customer’s financial lives
You have experience developing models, deploying them in a production environment, and integrating them into SaaS infrastructure
You have experience with cloud-based platforms such as AWS or GCP
You have strong communication skills, both written and oral



Joining the (lovely!) KOHO Team
We invest time and resources into making sure KOHO is as good as the people we hire. Here are some of the reasons we attract the best people:


• Balance Your Life - Generous PTO, generous vacation, and a lifestyle spending account

• Work Anywhere - Permanently remote and $1,000 to set up your home office

• Level Up - Access to an in-house certified performance coach

• Reach Your Goals - Salary assessments twice a year, annual training allowance
• The KOHO Culture - We have won 6 "Great Place to Work ®" awards since 2019

The KOHO culture is one of collaboration, creativity, and diverse perspectives. We are committed to building and fostering an inclusive, accessible environment for everyone. If you have any questions, concerns, or requests regarding accessibility needs, please contact peopleaccessibility@koho.ca and the People and Culture team will be happy to help. 

#LI-Remote #LI-DP1
Director Pricing Data Science at Divvy Homes

Why Divvy?


At Divvy Homes, we're building an on-ramp to homeownership – one that's more flexible, more affordable, and an all-around better fit for today’s American family – and it’s working.


We’re searching for a Director to lead Pricing Data Science at our growing company. Every day, Divvy must determine offer prices, rental prices, and buyback prices for thousands of homes. We are seeking an experienced data science leader to guide the team that builds and improves the models powering these decisions. 

In this role you will be responsible for setting and executing the overall strategic vision for pricing, finding new sources of data and modeling approaches to improve performance, communicating regularly with executives and stakeholders, hiring and mentoring IC data scientists, and sometimes contributing to IC work yourself. We’re looking for people who feel comfortable diving into difficult problems, getting their hands dirty, and getting results. You will report directly to our VP of Data Science & Analytics.


Skills & Experience

6+ years of experience working in data science, with 2+ years in management
Highly skilled in R, Python, or both
Previous experience working on an Automated Valuation Model (AVM) is preferred
Experience growing a team
Excellent communication for both technical and non-technical audiences



Perks

Competitive salary + equity
Full benefits (medical, dental, vision, 401k, commuter)
Position can be 100% remote, or on-site in our SF or Denver offices
Diverse, smart, and kind co-workers



Commitment to Diversity & Inclusion

Divvy Homes is committed to building a diverse and inclusive team. We enthusiastically encourage individuals from a variety of lived experiences to reach out.
Director Customer Data Science at Divvy Homes

Why Divvy?


At Divvy Homes, we're building an on-ramp to homeownership – one that's more flexible, more affordable, and an all-around better fit for today’s American family – and it’s working.


We’re searching for a Director to lead Customer Data Science at our growing company. Every day, for thousands of customer applications, Divvy must determine which of our products is most appropriate, underwrite potential risks, and set appropriate home shopping budgets. For existing customers, we must better understand drivers of success so that we can pull levers that help customers build equity toward homeownership. We are seeking an experienced data science leader to guide the team that owns the data science models powering these decisions. 

In this role you will be responsible for setting and executing the overall strategic vision for customer data science, understanding tradeoffs between information and friction in the underwriting process, finding new sources of data and modeling approaches to improve performance, communicating regularly with executives and stakeholders, hiring and mentoring IC data scientists, and sometimes contributing to IC work yourself. We’re looking for people who feel comfortable diving into difficult problems, getting their hands dirty, and getting results. You will report directly to our VP of Data Science & Analytics.


Skills & Experience

6+ years of experience working in data science, with 2+ years in management
Highly skilled in R, Python, or both
Previous experience working in underwriting or consumer credit is preferred
Experience growing a team
Excellent communication for both technical and non-technical audiences



Perks

Competitive salary + equity
Full benefits (medical, dental, vision, 401k, commuter)
Position can be 100% remote, or on-site in our SF or Denver offices
Diverse, smart, and kind co-workers



Commitment to Diversity & Inclusion

Divvy Homes is committed to building a diverse and inclusive team. We enthusiastically encourage individuals from a variety of lived experiences to reach out.
Machine Learning Scientist at Overjet

We take building our team and culture seriously, and how you do your work will be critical to the company we end up building. It’s important that we combine scientific ingenuity, engineering brilliance, and practical business judgement into the products that we bring to market.   
 
We are looking for an individual with a winning mix of creative energy, scientific innovation, and a practical mindset that is focused on building technology that is valuable to Overjet customers.  
 
You are joining Overjet at an interesting time as it is in the beginning stages of delivering revenue generating products to large sophisticated customers, while still being a small (sub 50 person) team where your contributions to the business will be outsized relative to larger more mature business. To be successful and happy at Overjet you will need to flourish in a fast-paced startup environment.



 
You will



Develop algorithms and methods for disease detection, classification, and characterization from x-rays 

Rapidly build proof-of concept prototypes and show what is possible with our products 

Focus on scalability and productionalization of the models 

Provide input and set boundary constraints for the machine learning infrastructure needed to scale our products 

Listen to the go-to-market team and ensure we are building product that fits demonstrated market needs






 
You are



Results oriented - you want to see your work impact the customer  

Ingenuous  - you can cleverly set up MVPs that work on the critical KPIs 

Endlessly curious  - in an earlier life you annoyed your family with one word: “Why” 

An experimentalist who learns by doing - You don’t abstractly wonder what is possible; rather, you rapidly test ideas and learn and iterate from feedback mechanisms






 
You have experience in



Prototyping computer vision models (CNNs in particular) - you have built both low and high fidelity concepts

Productionalizing CNNs - You don’t stop at the prototype.  You find it equally stimulating to mature the prototype at scale 

PhD or MS in Computer Vision, Machine Learning or related technical fields 
Knowledge of applied mathematics and numerical optimization


Applicants must be currently authorized to work in the United States.
Lead Data Scientist Emea M F D at Rain

ABOUT THE ROLE
Rain is looking for an experienced and passionate senior data scientist in our Data organization. This role will partner directly with product managers, engineers, marketing and other business partners across the business to research, develop, deploy and continuously improve the machine learning solutions to drive growth at Rain and improve user experience for our customers.
Responsibilities


Work with the risk and underwriting team to move from rules-based to predictive underwriting models


Create new predictive variables using your intuition, data insights, and automation techniques


Discover and evaluate the reliability of new data sources


Automate the creation of machine learning models


Underwrite customers and help define credit line limits and pricing


Thwart any fraudulent activities through superior data processes


Collaborate with business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.


Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.


Works closely with a team of frontend and backend engineers, product managers, and analysts.


Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.


Requirements


Fluent English


4+ years of experience in a data science role


Experience with or knowledge of R, SAS, Python, Matlab, SQL, noSQL, Hive, Pig, Hadoop, Spark


Able to build modern machine learning models using the aforementioned tools


Be an advocate for a data driven culture


Excellent problem solving and troubleshooting skills


Process oriented with great documentation skills


Excellent oral and written communication skills with a keen sense of customer service


BS or MS degree in Data Science, Computer Science or a related technical field


Knowledge of best practices and IT operations in an always-up, always-available service
Data Science Lead Us at Rain

We’re looking for a Data Scientist/Credit Modeler with startup experience to be our firstDS boots on the ground and launch our credit modeling function at Rain. You’ll wearthree hats: a high-performing individual contributor that will launch productionizedmodels, a leader that can build a data science team, with global dynamics, around youto tackle the unique challenges we’re facing, and a technically savvy strategic thinkerthat can be a thought partner to Credit, Product, and Engineering counterparts in settingup pipelines and other infrastructure to deploy insights at scale. Reporting through thecredit part of the organization, we’ll look to you to help develop and automate solutionsto complex business problems ranging from building credit models that touch on the fullcustomer lifecycle, to advanced forecasting, to customer segmentation, to optimizingpersonalized experiences on our platform.
Key Responsibilities● Identify and solve business challenges with advanced data science andanalytical tools● Partner with the credit team, product team, and engineering to translate businessinsights into productionalized models● Work cross functionally to design and set up the necessary pipelines andinfrastructure to deploy these productionalized models at scale throughout theorganization (inclusive of across numerous geographies)● Act as a thought partner to our senior leadership to help design and execute on awinning data-driven strategy● Understand and deploy the best tools/methods to effectively communicatecomplexities as needed to cross-functional teams
Skills:● 4-8 years of experience in a credit modeling or data science role● Degree in a quantitative field: economics, statistics, finance, computer science,or engineering● Expert in SQL and Python● Experience with pipeline development and model deployment (and maintenance)● Excellent communicator with the ability to explain ideas and concepts to DSnatives and novices alike● Entrepreneurial thinker with a bias for action● Experience working in a fast-paced, resource constrained, environment● Ability to successfully adapt and adjust to changes in business, regulatory, andeconomic environments● Firm understanding of personal finance and credit industry best practices● Ability to work under tight deadlines and exhibit grace under pressure● Desire to improve consumers' financial situation but ability to make toughdecisions
Data Scientist at Firebolt

Responsibilities

Build production ready machine learning models; your models will be the engine that powers all online commerce through Bolt
Conduct data analysis to determine which policies we adopt and help inform strategic growth
Build machine learning infrastructure, data pipelines and production ready services to serve live traffic
Work with other teams at Bolt to engineer new features for models or new product features that help improve Bolt business

Requirements

MS in Computer Science, Computer Engineering, or related field
4+ years of experience building large scale recommendation engines, ranking, and personalization systems
Thorough understanding of machine learning fundamentals and methodologies
Experience building and deploying machine learning models in an applied setting
Strong understanding of how to build scalable ML systems supporting online and offline applications
Experience working with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Spark ML
Familiarity with best practices of lifecycle management for ML models in industry
Mastery of a programming language such as Python, Java, Scala

Preferred

PhD in computer science or related field
Experience with big data technologies such as BigQuery, Spark, Dataflow, Apache Beam, Pubsub, Cloud Functions, EMR, S3, Glue, Kinesis Firehose, Lambda, etc.
Industry experience in building large-scale recommendation systems in a consumer-based setting.

Technical Experience

AWS Lambda for data ingestion and Kinesis Firehose to transport them into S3
Step functions and Lambdas to coordinate workflows
AWS Redshift as the data warehouse + Spark on EMR for doing ETL
Terraform for maintaining infra
Jenkins & CircleCI for build pipelines
Postgres RDS is our application database
Our code base is primarily in Golang & Typescript. However, our data bits are mostly in Python.

Check out our Engineering Blog!
Sr Data Scientist Marketing Acquisition at Rippling

About The Role
At Rippling, one of our core competitive advantages is the sheer number of products that we are able to offer our clients — over 20 SKUs and counting. This means that driving expansion revenue from cross-sell and upsell is critical to the company’s growth. We are investing heavily in this motion. That’s where you come in!
We’re looking for a seasoned analyst to help us answer questions such as: what types of customers are likely to purchase which products? What channels should we use to target what customers using what messaging and when?? This role will also partner closely with cross-functional teams to identify what metrics to measure for campaign success and deep dive into the data to provide insights for future campaigns/optimization.
As an early Data hire at Rippling, you’ll have the opportunity to dive into datasets to influence decision-making & impact strategy. If you are a self-starter who enjoys finding patterns and speaking through data, we’re looking for someone like you!
 
What You’ll Do:

Build full-cycle analysis using SQL, R, Python, or other scripting and statistical tools and present insights & learnings in verbal and written forms through BI tools, such as Tableau.
Report against our goals by identifying essential metrics and building executive-facing dashboards to track progress.
Proactively provide insights to help business and business leaders understand marketplace dynamics, user behaviors, and long-term trends.
Produce recommendations and use statistical techniques and hypothesis testing to validate your findings.
Identify and measure levers to help move essential metrics and make recommendations.
Collaborate with marketing teams (e.g. growth marketers, PMMs, and PMs) and product analytics teams to identify campaign success metrics, analyze campaign performance and user experience, and provide insights for campaigns/optimization.
Work autonomously as an individual contributor as well as showcase horizontal leadership, driving initiatives to completion and proactively identifying opportunities that will move the needle in the long run.

 
Qualifications:

5+ years of marketing analytics work experience with a Bachelor's Degree in Analytics, Data Science, Economics, Statistics or a related field.
Or 3+ years of marketing analytics work experience with a Master's Degree in Analytics, Data Science, Economics, Statistics or a related field.
Strong proficiency in SQL, R/Python, Tableau, or other Business Intelligence tools.
Ability to deliver actionable insights by synthesizing data into useful formats and conveying findings in a clear manner to influence decision-makers.
Ability to actively manage and influence stakeholders through strong business communication skills, both verbal and written forms.
Ruthless prioritization and time management.
Organized, attentive to detail, and intellectually curious.
Experience in marketing campaign analysis focusing on cross-sell and up-sell through email & in-product channels preferred.
Experience with B2B SaaS companies preferred.
Sr Data Scientist Marketing Analytics Cross Sell at Rippling

About The Role
At Rippling, one of our core competitive advantages is the sheer number of products that we are able to offer our clients — over 20 SKUs and counting. This means that driving expansion revenue from cross-sell and upsell is critical to the company’s growth. We are investing heavily in this motion. That’s where you come in!
We’re looking for a seasoned analyst to help us answer questions such as: what types of customers are likely to purchase which products? What channels should we use to target what customers using what messaging and when?? This role will also partner closely with cross-functional teams to identify what metrics to measure for campaign success and deep dive into the data to provide insights for future campaigns/optimization.
As an early Data hire at Rippling, you’ll have the opportunity to dive into datasets to influence decision-making & impact strategy. If you are a self-starter who enjoys finding patterns and speaking through data, we’re looking for someone like you!
 
What You’ll Do:

Build full-cycle analysis using SQL, R, Python, or other scripting and statistical tools and present insights & learnings in verbal and written forms through BI tools, such as Tableau.
Report against our goals by identifying essential metrics and building executive-facing dashboards to track progress.
Proactively provide insights to help business and business leaders understand marketplace dynamics, user behaviors, and long-term trends.
Produce recommendations and use statistical techniques and hypothesis testing to validate your findings.
Identify and measure levers to help move essential metrics and make recommendations.
Collaborate with marketing teams (e.g. growth marketers, PMMs, and PMs) and product analytics teams to identify campaign success metrics, analyze campaign performance and user experience, and provide insights for campaigns/optimization.
Work autonomously as an individual contributor as well as showcase horizontal leadership, driving initiatives to completion and proactively identifying opportunities that will move the needle in the long run.

 
Qualifications:

5+ years of marketing analytics work experience with a Bachelor's Degree in Analytics, Data Science, Economics, Statistics or a related field.
Or 3+ years of marketing analytics work experience with a Master's Degree in Analytics, Data Science, Economics, Statistics or a related field.
Strong proficiency in SQL, R/Python, Tableau, or other Business Intelligence tools.
Ability to deliver actionable insights by synthesizing data into useful formats and conveying findings in a clear manner to influence decision-makers.
Ability to actively manage and influence stakeholders through strong business communication skills, both verbal and written forms.
Ruthless prioritization and time management.
Organized, attentive to detail, and intellectually curious.
Experience in marketing campaign analysis focusing on cross-sell and up-sell through email & in-product channels preferred.
Experience with B2B SaaS companies preferred.
Senior Manager Data Analytics at Modernize

Job Category
As a key member of the Strategic Marketing & Analytics team, you will be responsible for data-driven insights that enable QuinStreets Marketing and Media teams to maximize profitability while developing customer relationships. You will gather, organize, and aggregate complex sets of data in order to produce meaningful business insight in areas such as ad network optimization, ad merchandising, marketing performance, quality monitoring, partner development, product testing, and more. You will also communicate your insights and findings to various members of our Client, Media, Analytics, and Executive teams.
 
Responsibilities

Work closely with media and client managers to understand business opportunities for media, client and market growth.
Actively mine data to develop actionable insights from our proprietary datasets using various statistical techniques.
Evaluate strategies and forecast their expected impact to the key performance indicators.
Support analysis and monitoring of business metrics and trends.
Key liaison between business and technical teams in managing day to day data analytics.

 
Qualifications:

Record of high academic achievement with a BS degree in Business, Economics, Engineering, Math/Science, or otherwise proven background in business/analytics. MS preferred.
5+ years of work experience in data analytics/science.
Strong understanding of statistical methods used in to elicit insights from data.
Strong analytical mindset with a drive toward actionable insights from data.
Deep interest in online marketing and media industry. Industry experience a plus.
High internal motivation with ability to understand the full stack of product development.
Willingness to initiate and own research, exploration, and analysis from start to finish for any business problem.
Good interpersonal skills and ability to remain focused-yet-flexible in a fast-paced internet company environment.
Proficiency in MS Excel, Tableau and SQL.
Familiarity with Python (preferred) or R programming to the level necessary to perform ad-hoc analysis.

 
#LI-REMOTE
Data Scientist at Luckbox

Are you passionate about solving real-world challenges using cutting-edge artificial intelligence (AI) and machine learning (ML) technology? You will be part of an ambitious team of scientists and software engineers with the goal of creating better products for our customers. You and your team will work to develop proof of concepts and transition promising new technology into products. As a Data Scientist, you will have the opportunity to explore exciting and diverse data, work with cutting-edge algorithms and technologies and participate in the development of solutions that generate new insights and products for the gaming industry.

If you are a self-driven, highly motivated and driven by success then this is the role for you.

Responsibilities: 
Manage and execute analysis pipelines using cloud computing platforms such as AWS
Independent creation of forecast models and support for the implementation of these models in the existing processes 
Use of state-of-the-art methods for data analysis and modelling (especially from the areas of machine learning, statistics, data mining and time series) 
Independent management of data projects and coordination with the requirements of various stakeholders 
Communication of the results obtained to the management 
Collaborate with talented data scientists, data engineers, software developers, and other stakeholders in an agile environment.
Quantitative Markets Analyst at Affirm

We’re looking for a smart, driven individual to join our Quantitative Markets team. The Quantitative Markets team is responsible for structuring and pricing Affirm’s debt funding deals, developing platforms and tools for optimizing funding strategies, and building data-driven models to analyze and predict the performance of Affirm’s consumer loans. The ideal candidate has the strong technical skills required to develop and implement quantitative and/or machine learning models.

What you'll do

Ensure the resiliency of new and existing funding agreements by enhancing and expanding the team's suite of structuring, monitoring, and analysis capabilities
Develop automation tools and optimize models to create operating leverage for the team and the business
Provide insights on capital markets deals to cross-functional teams to enable more optimal and efficient funding strategy and merchant pricing
Work closely with the Capital Markets team to evaluate, structure and price consumer asset-backed transactions
Build data-driven models to analyze and predict the performance of Affirm’s consumer loans
Partner cross-functionally with our Treasury, Capital Markets, Risk, Commercial, Product and Engineering teams to evaluate funding, product, and business decisions


What we look for

1-3 years of relevant experience in technical areas (e.g. data science, data analytics, quantitative finance).
Intellectual curiosity, a growth mindset, and an emphasis on relentless self improvement
Strong data-manipulation and model development and implementation skills using tools such as Python/R
Experience building quantitative models or implementing machine learning models is a plus
Strong interpersonal and communication skills, and ability to collaborate and influence across different teams in the organization
Desire to understand the broader context of business decisions
Ability to think creatively and critically and thrive in a fast-paced, dynamic, and often ambiguous work environment




Location - Remote U.S.
Grade - USA28


#LI-Remote
Principal Decision Scientist at Atlassian

Working at Atlassian
Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or return to an office as they reopen (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Your future team
Atlassian is looking for a Principal Decision Scientist with technical skills to join the Decision
Science team and own our total customer potential model(s) and strategy.
What you'll do
Work with both technical and non-technical partners across Marketing and Product to clarify Atlassian's future potential and identify levers to access that potential.Expand the existing model to use dynamic features and flexible outputs to solve the use cases of more partners.Find ways to measure the incrementality of levering the model through experimentation and funnel analysisEmpower partners by giving them the ability to self-serve using Tableau dashboardsApply creative analytical skills to several types of business questions to deepen our understanding around the potential and propensity of each Atlassian customer
Your background
8 + years of experience in analytics or related fields4 + years of experience in potential/projection modeling2 + years of experience in attribution, incrementality or experimentationA track record for creating raw data and analysis into well-written contentComfort with structuring and coaching others to work through open-ended business questions through analyticsAdvanced proficiency in SQLA willingness to learn and adapt to new technologies and methods as needed
Senior Manager Data Management at Atlassian

Working at Atlassian
Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or return to an office as they reopen (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Your future team
We're looking for a Data leader with business instincts, management experience, analytics mastery, and experienced in improving data science efficiency. Someone who is passionate about applying these skills to lead data quality, reduce the need for data scientists to perform data engineering tasks, working across the organization to create the proper data layer to increase data science productivity.
What you'll do
Develop relationships with leaders across data science, data engineering, data platform, and other teams to understand and influence requirements that support the strategic goals of Atlassian.Guide the creation of tools that allow a centralized data framework that improves the efficiency, quality and capabilities of all data analysts and scientists.Develop business cases and roadmaps for transformational data projects that unlock the potential of the team.Partner with the data engineering and platform teams to Identify, and support short, medium and long-term portfolio of projects that satisfies the data layer and quality roadmapsWork across marketing and product to develop monitoring and action plans across the data quality lifecycle (instrumentation → transformation → data/metrics/segments)Lead, coach, and build the data quality team within the Data Science teamCollaborate with the Business Intelligence team to define and achieve standard segment and metric definitions and governance.Contribute into overall Data Science team OKRsBe part of building an outstanding analytics culture at Atlassian. Leading by example, through education and creation of self-service tools, to make a lasting change in how data is used to make decisionsAbility to explain data science concepts to diverse audiences, and build decision confidence by sharing expertise of facts and uncertainties
Your background
3+ years of data science, analytics and/or data engineering leadership experienceExperience applying analytics knowledge to work across data science, engineering, and platform teams to deliver foundational data layers.An Agile development mentality, appreciating the benefit of constant iteration and improvementA very high bar for output quality; with experience coaching teams to balance thoughtfulness, perfection and speedFamiliarity working with Data Engineering, Product Management, Engineering, and Data Platform teams.Expertise in data manipulation and statistical programming languages (e.g. SQL, R, Python), and knowledge of cloud data environments (e.g. AWS)An understanding of the SaaS development, business model and metricsExperience in A/B experimentationA degree in a quantitative field (e.g. statistics, mathematics, physics, econometrics, or computer science)
Senior Manager Web Analytics And Data Science at Atlassian

Working at Atlassian
Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or return to an office as they reopen (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Your future team
Our Customer Analytics team is comprised of individuals with backgrounds in data science and analytics. We collect, organize and analyze data to help our business partners make informed decisions.
We're looking for an Analytics & Data Science leader (Manager or Senior Manager) with business instincts, team development, creativity and analytics mastery. Someone who is passionate about applying these skills to lead multiple analytics teams, guide smarter product decisions, and delight our customers. This is a role that will stretch you, accelerate your learning curve and give you the chance to really leave your mark in the history of Atlassian.
What you'll do
Collaborate with Atlassian's product leaders (responsible for www.atlassian.com, support.atlassian.com & community.atlassian.com) to provide data-driven viewpoints on strategic decisions, identify high impact opportunities for analysis and align priorities with the company strategy and product roadmapLead a team of data scientists and plan roadmaps by collaborating with product partners, customer research, data engineers, machine learning engineers and other data scientistsDesign targeted explorations of our big data, to understand trends, find opportunities, and make recommendations to improve user journeys and customer valueAccelerate web experimentation through best practices, tooling and clear recommendationsBe part of building an outstanding analytics culture at Atlassian. Leading by example, through education and creation of self-service tools, to make a lasting change in how your partners use data to make decisions
Your background
3+ years leading analytics or data science teamsExperience applying your analytics to projects which have had a positive impact to company level business and product decisionsA very high bar for output quality; with experience coaching teams to balance thoughtfulness, perfection and speedCraft compelling insights, explaining data science concepts to diverse audiences, and building decision confidence by sharing expertise of facts and uncertaintiesFamiliarity partnering with multiple departments. For example: Product Management, Engineering, Design, Finance, Customer Research and Data Engineering teamsExperience encouraging teamwork in a "work from anywhere" environmentPrevious experience in data manipulation and statistical programming languages (e.g. SQL, R, Python), and knowledge of cloud data environments (e.g. AWS)Varied experience applying a range of data science techniques (eg: exploratory data analysis, experiment design, propensity modeling or attribution)An Agile development mentality, appreciating the benefit of constant iteration and improvement
Senior Machine Learning Researcher For Copilot at Github

GitHub is looking for a research engineer in the area of machine learning to join GitHub Next.
We are a growing team of engineers and researchers. Having made our mark with high-impact success stories like GitHub Copilot, we want to keep leveraging the power of Machine Learning to revolutionize GitHub and hence the world-wide community of developers and creators who rely on it for their daily work. We continue to build on these foundations while at the same time exploring new projects in different areas including AI-enhanced static analysis, supply-chain security, innovative approaches to CI, and many more.
You will be working with other members of our team as well as colleagues from elsewhere in  GitHub and Microsoft on providing machine learning solutions to these challenges. Some of the projects at the Innovation Lab are a sustained effort to put an idea that has proven its worth into production and at the fingertips of the world’s developer community, whereas others are an experimental evaluation of a new idea where we iterate quickly to separate ideas that show promise from those that need some more time to mature. While we are not primarily a research outfit, our work does regularly yield novel results and insights along the way, which we publish at academic conferences where applicable.
Responsibilities:

Participate in our ongoing projects in the area of code intelligence.
Conceive, design, train and deploy machine learning models.
Extend and fine-tune deep learning architectures.
Help out in the day-to-day running of the Innovation Lab: organizing our webinar series, interviewing new candidates, and disseminating research results.

Minimum Qualifications:

Firm theoretical background in machine learning.
3 years+ hands-on machine learning experience.
Previous experience with deep learning, sequence models and NLP.
Inclination to prototype quickly and make fast decisions on experiment failure.

A creative mindset and good practical skills are more important to us than formal experience.
Preferred Qualifications:

PhD in computer science, mathematics, or a related field, or other evidence of the ability to do independent, innovative research.
Previous experience at working with large, distributed machine learning pipelines, e.g. using Microsoft Azure or k8s.
Experience training large language models for code generation.
Ability to communicate complex ideas clearly, both in spoken and written form, for expert as well as novice audiences.

 
(Colorado only*) Minimum salary of $118,100 to maximum $286,000 + bonus + equity + benefits.· Note: Disclosure as required by sb19-085 (8-5-20) of the minimum salary compensation for this role when being hired in Colorado. 

Location: In this role, you can work remotely from anywhere in the United States or onsite in one of GitHub’s U.S. offices (San Francisco, Bellevue, Raleigh)
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