nathansutton/data-science-job-descriptions huggingface dataset:
Senior Economist Pricing at Thrasio

Wild Thinkers Welcome
 
Thrasio is a next-generation consumer goods company reimagining how the world’s most-loved products become accessible to everyone. We acquire quality brands and use world-class expertise and data science to make existing products better or create new ones to meet customer needs.  

We’ve got huge goals, and every Thrasher plays an integral part in getting us there. That’s why we only bring on people who think positively. Who look out for the team. Who tell their egos to take a hike while they get the job done right. 
 
From the moment you become a Thrasher, we give you the freedom you need to take big swings and push what’s possible to get us there. And if you fail, it’s cool—we know you’ll grow spectacularly. What matters is that you’re helping impact millions of people around the world who use our products everyday. 
 
Because with every new spatula or pillow brand we grow, with every kitchen scale we develop, our goal is to provide people everywhere with what they need to make the most of every moment - ensuring that what gets delivered to their door delivers.

As a Senior Economist on the Pricing & Promotions team, you will own a causal modeling framework to estimate contextual price elasticities and promotional lifts over Thrasio’s extensive portfolio of omnichannel products to drive optimal pricing & promotions decisions, which is fundamental to Thrasio’s long-term success. 


Responsibilities: 

Leveraging state of the art causal inference methodology to measure price elasticity and promotional lifts with observational and experimental data
Designing experiments to improve measurement and validate strategies
Developing integrated solutions across pricing, promotions, marketing, forecasting, and supply chain
Collaborating with cross-functional partners to build the best pricing solutions
Driving strategic initiatives across the broader org as a leader at Thrasio
Owning team development cycles, managing risk, and bringing stakeholders along for the ride



Requirements:

Masters or Ph.D. in Economics or a related field such as Quantitative Marketing or Finance
2+ years of practical experience working with panel data (ideally in e-commerce)
Expertise in econometrics, causal inference, and experiment design
Proficiency in Python, SQL, Git
Passion for driving outsized business impact through applied science



Nice to have: 

Expertise in Structural Modeling, Operations Research, Machine Learning
Familiarity with Git, Databricks, Snowflake, Spark



THRASIO IS PROUD TO BE AN EQUAL OPPORTUNITY EMPLOYER AND CONSIDERS ALL QUALIFIED APPLICANTS FOR EMPLOYMENT WITHOUT REGARD TO RACE, COLOR, RELIGION, SEX, GENDER, SEXUAL ORIENTATION, GENDER IDENTITY, ANCESTRY, AGE, OR NATIONAL ORIGIN. FURTHER, QUALIFIED APPLICANTS WILL NOT BE DISCRIMINATED AGAINST ON THE BASIS OF DISABILITY, PROTECTED CLASSES, OR PROTECTED VETERAN STATUS. THRASIO PARTICIPATES IN E-VERIFY. 

Thrasio does not accept agency resumes. Please do not forward resumes to our jobs alias, Thrasio employees or any other organization location. Thrasio is not responsible for any fees related to unsolicited resumes.
Principal Economist at Thrasio

Wild Thinkers Welcome
 
Thrasio is a next-generation consumer goods company reimagining how the world’s most-loved products become accessible to everyone. We acquire quality brands and use world-class expertise and data science to make existing products better or create new ones to meet customer needs.  

We’ve got huge goals, and every Thrasher plays an integral part in getting us there. That’s why we only bring on people who think positively. Who look out for the team. Who tell their egos to take a hike while they get the job done right. 
 
From the moment you become a Thrasher, we give you the freedom you need to take big swings and push what’s possible to get us there. And if you fail, it’s cool—we know you’ll grow spectacularly. What matters is that you’re helping impact millions of people around the world who use our products everyday. 
 
Because with every new spatula or pillow brand we grow, with every kitchen scale we develop, our goal is to provide people everywhere with what they need to make the most of every moment - ensuring that what gets delivered to their door delivers.

As a Principal Economist on the Pricing & Promotions team, you will own a causal modeling framework to estimate contextual price elasticities and promotional lifts over Thrasio’s extensive portfolio of omnichannel products to drive optimal pricing & promotions decisions, which is fundamental to Thrasio’s long-term success. 


Responsibilities: 

Leveraging state of the art causal inference methodology to measure price elasticity and promotional lifts with observational and experimental data
Designing experiments to improve measurement and validate strategies
Developing integrated solutions across pricing, promotions, marketing, forecasting, and supply chain
Collaborating with cross-functional partners to build the best pricing solutions
Driving strategic initiatives across the broader org as a leader at Thrasio
Owning team development cycles, managing risk, and bringing stakeholders along for the ride



Requirements:

Masters or Ph.D. in Economics or a related field such as Quantitative Marketing or Finance
5+ years of practical experience working with panel data (ideally in e-commerce)
Expertise in econometrics, causal inference, and experiment design
Proficiency in Python, SQL, Git
Passion for driving outsized business impact through applied science



Nice to have: 

Expertise in Structural Modeling, Operations Research, Machine Learning
Familiarity with Git, Databricks, Snowflake, Spark



THRASIO IS PROUD TO BE AN EQUAL OPPORTUNITY EMPLOYER AND CONSIDERS ALL QUALIFIED APPLICANTS FOR EMPLOYMENT WITHOUT REGARD TO RACE, COLOR, RELIGION, SEX, GENDER, SEXUAL ORIENTATION, GENDER IDENTITY, ANCESTRY, AGE, OR NATIONAL ORIGIN. FURTHER, QUALIFIED APPLICANTS WILL NOT BE DISCRIMINATED AGAINST ON THE BASIS OF DISABILITY, PROTECTED CLASSES, OR PROTECTED VETERAN STATUS. THRASIO PARTICIPATES IN E-VERIFY. 

Thrasio does not accept agency resumes. Please do not forward resumes to our jobs alias, Thrasio employees or any other organization location. Thrasio is not responsible for any fees related to unsolicited resumes.
Network Data Scientist at Altana

The Financial Services team is looking for talented Network Data Scientists to help execute this vision. You’ll work closely with our Clients, Data Scientists, Product Managers, Software Engineers, and leadership team to develop analytics that provide insights on network dynamics and their impacts on financial performance in supplier networks.
 
Responsibilities

Develop statistical models of network structures and their relationships to network behavior
Automate identification of persistent network structures as well as emergent network structures and behaviors
Build analytical solutions for understanding network dependencies
Establish metrics for common network attributes such as attachment, centrality, connectivity, distance, path lengths, and similarity
Develop new metrics that describe network characteristics as relates to the performance of businesses in the network 
Develop models to describe, predict, and simulate network behavior under multiple scenarios 
Categorize relationships between network patterns and business outcomes
Build descriptive and predictive models of network dynamics that can be used to plan business strategies by people regardless of their expertise in network analytics


About You

BS, MS, or PhD degree in Computer Science, Data Science, Economics, Statistics, Computational Biology, BioInformatics, or equivalent experience
You have a strong background in data science, graph mining, and graph simulations
You enjoy sharing your expertise using Python for graph analysis and machine learning
You have experience with data intensive applications and complex systems
You are energized by power laws, long-tail effects, and nonlinear system dynamics 
You are comfortable communicating technical analysis to less technical stakeholders
You are interested in applying network analysis to improve the world
You have strong written and verbal communication skills

 
Nice to have, but not required

Experience with Apache Spark, Databricks
Experience with generative models of network structure and behavior
Experience analyzing supplier networks in supply chains, banking, insurance, or ecommerce

 
Technologies we love

Languages: Python, Spark, SQL
Tools: Scikit-learn, Numpy, Pandas, NetworkX, PyTorch, Tensorflow, DGL
Datastores: Databricks, Elasticsearch, Postgres, RDS, Kafka
Staff 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!
Data Scientist at Sportradar

Synergy Sports, A Division of Sportradar, is looking for a talented Data Scientist to join our software team.
Synergy Sports delivers on-demand analytics and associated video to nearly 1500 basketball, baseball, and hockey teams from pro, international, and college leagues. Our systems are highly complex and contain petabytes of data and video requiring extremely capable individuals to maintain the scale and efficiency of its products.
Synergy Sports’ data science team will contribute to the ongoing development of the company’s revolutionary sports data and video delivery solutions, building applications such as:
Sports Workflow ApplicationsSports Analytics Systems
Synergy Sports is a globally distributed company, with employees working from home offices. The role must be comfortable working in a virtual office using online collaboration tools, with all communication and interaction in English. We work on an asynchronous model with flexibility of when and where you want to perform your job, while still being able to attend team calls and regular meetings. Personal initiative and a strong work ethic are highly encouraged and rewarded.
The company provides a very transparent freedom and responsibilities culture to all our teams. We strongly believe striking the balance between work and family is very important and our culture is focused on the well-being of our team.
Requirements
5+ years of experience in data science or data engineering related roleDemonstrated, creative problem-solving using data analysisApplied experience with regression analysis and other statistical modeling techniquesStrong proficiency in PythonFundamental understanding of Machine learning concepts (e.g. cross-validation, statistical basis for ML algorithms, etc..)
Bonus Superpowers:
Experience scaling and operationalizing data science models in production settingsExperience working with MongoDB, MySQL, or other relational/noSQL databasesSoftware engineering backgroundSport-specific analytics experiencePrevious experience leading a team
Benefits
Big problems, massive impact. We’re working on big scalability challenges and our flat structure means individuals have an incredible amount of impact on everything they touch.Join our team of best-in-class engineers to disrupt the sports industry and learn, share and grow with great peers on a daily basis.A culture geared towards innovation and experimentation. From Deep learning and Computer vision to Kubernetes and the latest cloud technologies.Competitive salary based on your experience.
Sr Data Scientist Machine Learning Ads Quality at Reddit

We are looking for a Machine Learning Data Scientist to work within the Ads Data team. You will work closely with engineers and product owners from our Ads team to 1) optimize ads delivery and auction systems, 2) shape product roadmap and strategy of ads quality and relevance. This person has a solid business acumen and knows what is important to advertisers and users (i.e. redditors). In addition, this person needs to demonstrate strong cross-functional stakeholders management capabilities. 
Reddit is continuing to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.
Responsibilities:

Research, design and develop contextual ad relevance models. Reddit ad is a combination of text, image, user and ad engagement attributes. You will use modern deep learning techniques to combine those signals to measure ad quality. 
You will design metrics and mechanisms to understand different tradeoffs between user engagement and ad quality. You will develop algorithms that would optimize both ad quality and ad delivery. 
Be involved in all phases of modeling such as ideation, offline modeling, online implementation, experimentation, deploy and post-launch monitoring/measurements.
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. 
Serve as a thought-partner for product managers, engineering managers and leadership in shaping the monetization roadmap and strategy for Reddit by identifying opportunities through deep-dive analyses and/or modeling.

What We Can Expect From You:

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
4+ years of experience (for Bachelor’s/Master’s); 2+ years of experience (for Phd) in quantitative/modeling roles, preferably for a consumer-facing service/app
Proficiency in machine learning, statistical modeling, and optimization
Understanding of experimentation and causal inference analyses
Strong analytical and communication skills
Familiarity with at least one of the Deep Learning platforms (e.g. Pytorch, Tensorflow)
Computer vision experience strongly preferred
Strong skills in SQL and programming (Python or R) 
Experience in online advertising is preferred but not required
Data Scientist Lead Payments at Level

What You'll Do:

Build, optimize, and scale money-moving systems across all of our products and users
Drive strategic deals and integrations with partners across the payments ecosystem, including banks, credit card networks, and processors
Reconcile payments data between systems, banks, and processors
Develop a data-driven roadmap for new financial products
Collaborate with cross-functional teams including engineering, data science, finance, and operations
Help us rethink how businesses and people pay for and use their employee benefits
Identify and scope product challenges that are ripe for data science solutions—like risk modeling, data-informed insurance plan design, dentist search optimizations
Work cross-functionally to inform data collection, productionize data science work, and integrate machine learning into the product

Who You Are:

4+ years of payments, finance, or consulting experience
5+ years of industry experience in relevant roles such as data scientist, data analyst, or data engineer
Expertise with payments infrastructure (ACH) and reconciliation (AR/AP)
Experience working with and building API integrations with large partners
Strategic thinking, problem solving, and analytical skills
Clear and effective communication style
An ownership mentality, eager to grow in an early-stage company
Prior experience in risk modeling, forecasting, or working with time series data
Prior experience working with dirty or high-dimensional, categorical data
Experience with SQL, proficiency in one scripting language like R or Python working in a collaborative development environment, and willingness to pick up new programming languages.
Experience working with highly confidential information.
Bonus: Prior experience working with healthcare and insurance data, and experience leading a team of Data Scientists and Data Analysts.

Our technologies:
 
These are some of the technologies we use today. You don’t need to be familiar with all of these; many people on our team learned them with us. During our interview process, you’re welcome to use any language you’re most comfortable with.


Languages and libraries - Python, Go, Protobuf, gRPC
Amazon Web Services (AWS) - Relational Database Service (RDS), S3, Elastic Kubernetes Service (EKS), Sagemaker
Google Cloud Platform (GCP) - BigQuery
GitLab
ElasticSearch
Looker


What We Offer:

Have the chance to work at a leading innovator and trailblazer in the world of insurance and payments.
Competitive salary and equity
100% paid medical for you and 80% for your dependents, 100% covered dental and vision through Level for you and your dependents
Flexible vacation policy - take the time you need when you need it!
Fully Paid Parental leave for 3 months
Quarterly Company sponsored events
Internal learning and development programs
Data Scientist Risk at Level

What You'll Do:


Identify and scope product challenges that are ripe for data science solutions—like risk modeling, data-informed insurance plan design, dentist search optimizations
Work cross-functionally to inform data collection, productionize data science work, and integrate machine learning into the product
Drive new features and improvements across all our products and services by finding innovative ways to use data to help customers
Build the infrastructure that allows us to scale by defining analytic requirements, developing analysis plans, and ensuring data quality standards

Who You Are:

5+ years of industry experience in relevant roles such as data scientist, data analyst, or data engineer
Strong product sensibilities
Critical thinking, problem solving, and analytical skills
Clear and effective communication style
Prior experience in risk modeling, forecasting, or working with time series data
Prior experience working with dirty or high-dimensional, categorical data
Prior experience productionizing data science work
Experience with SQL, proficiency in one scripting language like R or Python working in a collaborative development environment, and willingness to pick up new programming languages
Bonus: Prior experience working with healthcare and insurance data, and experience leading a team of Data Scientists and Data Analysts

Our technologies
These are some of the technologies we use today. You don’t need to be familiar with all of these—many people on our team learned them with us. During our interview process, you’re welcome to use any language you’re most comfortable with.

Python
MySQL
GitLab
Amazon Web Services (AWS)
ElasticSearch
Kubernetes
Looker
Go
Protobuf / gRPC

What We Offer:

Have the chance to work at a leading innovator and trailblazer in the world of insurance and payments.
Competitive salary and equity
100% paid medical for you and 80% for your dependents, 100% covered dental and vision through Level for you and your dependents
Flexible vacation policy - take the time you need when you need it!
Fully Paid Parental leave for 3 months
Quarterly Company sponsored events
Internal learning and development programs
Data Science Intern at Level

Please Note: This is a Fall 2022 (Sept - Dec 2022) Internship
 
What You'll Do:

Build data-driven products such as fraud detection systems, insurance plans, and dentist search optimizations.
Work cross-functionally with engineering, clinical, and operations to inform data collection, productionize data science work, and integrate machine learning into the product
Drive new features and improvements across all our products and services by finding innovative ways to use data to help customers
Work on building the data model our platform will use to organize information for online and offline use

Our technologies: 
These are some of the technologies we use today, but they aren't a requirement. Many successful members of our team learned them with us. During our interview process, you are free to use any language you're most comfortable with.
- Python
- Go
- Kubernetes
- Protobuf / gRPC
- AWS
- SQL
- ElasticSearch
What We Offer:

Mentorship from day 1 to help acclimate you to the company and ensure you're set up to succeed
Frequent feedback on projects to help fuel growth and success
Ability to learn new technologies and work on projects based on your current skillset and growth goals
Participation in decisions that go into launching the product
Opportunity to work closely with a team that collectively has decades of experience in the tech industry
Social hour every two weeks
Competitive compensation
Travel to NYC for team events
$100 monthly food stipend
$200 home/office set-up reimbursement
Senior Performance Marketing Data Science Manager 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.
Does the challenge of scaling a fast-growing company by powering it with data, reporting, and analytics excite you? Using your business instincts and creativity, you will support a best-in-class product with nuanced analysis, actionable insights, and strong recommendations. We're growing quickly, so you'll need to help define, implement, and scale the systems and processes for sustainable growth across the Marketing and Data Science organizations. If you love finding patterns amidst chaos, making quick decisions, and aren't afraid of being wrong, then this role could be a great fit!
We're looking for a Senior Manager with strong technical and leadership skills to lead our Performance Marketing Data Science team. I
In this role, you will:
Partner with one of Atlassian's most data driven teams to measure performance and identify opportunities within Paid Advertising, Content Marketing & Email.Apply creative analytical problem solving skills to a wide variety of questions to deepen our understanding of marketing channel effectiveness.Work cross functionally with Data Engineering, Machine Learning and Operations teams to bring data to the forefront of marketing decision making.Build and lead a high performing team of data scientists (team of 5 today with significant growth planned). 
On the first day, we'll expect you to have:
6 + years of experience in analytics or closely related fields2 + years of experience managing teamsA passion for building analytics frameworks to measure new and open ended business strategiesExperience with marketing measurement techniques including channel attribution, lifetime value/mROI and incrementality testing. A proven track record for crafting raw data and analysis into well-written and persuasive contentThe ability to prioritize your time wisely against multiple competing projects and requestsComfort 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
It's great, but not required, if you have:
Experience with at least one analytics & visualization tool such as Tableau, Looker, Mode, Plotly, etc.Experience with scripting and analysis languages (Python, R)Familiarity with statistics and probability
Data Scientist Talent Acquisition 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.
Does the challenge of scaling a fast-growing company by powering it with data, reporting, and analytics excite you? Using your business instincts and creativity, you will partner with other analysts to help support best-in-class talent acquisition with nuanced analysis, actionable insights, and strong recommendations. We're growing quickly, so you'll need to help define, implement, and scale the systems and processes for sustainable growth across the talent acquisition and analytics organizations. If you love finding patterns amidst chaos, making quick decisions, and aren't afraid of being wrong then this role could be a great fit!
On the first day, we'll expect you to have:
3-5 years of experience in HR/recruiting analytics or closely related fieldsProficiency in reading and writing SQL queriesA strong intuition for crafting raw data and analysis into well-written and persuasive contentThe ability to prioritize your time wisely against multiple competing projects and requestsExperience translating insights into decisions and actions that have a direct business impactComfort working with remote teammates and remote-friendly workflowsExperience with at least one analytics & visualization tool such as Tableau, Looker, Mode, Plotly, etc.A willingness to learn and adapt to new technologies and methods as needed
It's great, but not required, if you have:
Experience with HR and recruiting in high-growth companiesExperience with scripting and analysis languages (Python, R)Experience with GitExperience with providing analytics support for recruiters and leadership teamsFamiliarity with statistics and probability
Machine Learning 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.
Atlassian is looking for a Machine Learning Scientist specializing in search to join our Core ML team! You will be a member of the Core ML team but also partner with the Search Platform team to help to build out the machine learning and data science capabilities to provide our Atlassian customers with a fast, relevant search experience.
Your work will impact millions of users across a whole suite of Atlassian products as you define the foundations for how teams find what they are looking for. This position offers a unique opportunity to work in an exciting environment by implementing cutting-edge machine learning techniques to solve tough, yet unique problems in the enterprise search space.
In this role, you'll get to:
Tune the search strategy across a large variety of information retrieval use cases and query intentsApply and refine optimization and NLP techniques to enable a more personalized, customized search using behavioral data and user-generated contentDesign and execute experiments to test hypotheses for improving the relevance of search resultsWork with our seriously large volume of analytics data to understand insightful trends and behaviorsCraft machine learning and predictive models to drive intelligent product features
On your first day, we'll expect you to have:
Bachelor or higher degree (or equivalent) in a quantitative subject (statistics, mathematics, computer science, engineering, or physics)Industry experience in the data science or machine learning domainDevelopment experience in a programming language, Python is strongly preferredExpertise in SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)Experience developing, building, and scaling machine learning models in business applications using large amounts of data. Previous experience in search or recommender systems is highly regardedAbility to communicate and explain data science and machine learning concepts to diverse audiences and craft a compelling storyFocus on business practicality and the 80/20 rule; very high bar for output quality but recognize the business benefit of “having something now” vs “perfection sometime in the future”Agile development approach, appreciating the benefit of review, constant iteration, and improvement within a collaborative team environment
It's great, but not required if you have:
Experience working in an enterprise or B2B space for a SaaS product provider, as well as the consumer or B2C spaceExperience with information retrieval and solving complex search relevance and ranking problemsFamiliarity with search technologies including ElasticSearch, Solr or otherwiseKnowledge of advanced machine learning and deep learning methods applied to digital user behaviours
Data Scientist Us at Andela

About the role
Andela’s two-sided marketplace is a multifaceted hub of experienced talent and leading companies with exciting challenges related to pricing, matching, marketplace health, go-to-market campaigns and many others. Data Science is a key weapon at Andela to attack these problems. We employ a wide variety of approaches including but not limited to system dynamics and simulation, machine learning on both structured and unstructured data, recommendation algorithms, and combinatorial optimization. A Data Scientist at Andela will be involved in building ground breaking solutions often embedded in products serving both the marketplace and various business functions. You will be defining solution architecture, crafting the appropriate machine learning / optimization / experimentation model and guiding the execution of this model in collaboration with the Andela data, engineering and product teams.
Responsibilities:

Work with the Principal Data Scientist and other business partners to identify problem domains and corresponding data science approaches
Develop the Minimum Viable Product (MVP) version of the solution
Deploy the solution in production in collaboration with the data, engineering and product teams

Requirements:

Graduate degree (MS/Ph.D.) in quantitative field such as Economics / Statistics / Operations Research / Computer Science
2-3 years work experience applying quantitative methods to business problems
Flexibility in working with a variety of data science approaches
Hands-on with coding, Python strongly preferred
Nice-to-have: proficiency in mathematical modeling

#LI
Data Scientist Insurance at Kin

So, what’s the role?
At Kin, we are modernizing and simplifying a 100-year-old industry through the use of data & technology. The data science team at Kin is a centralized department supporting the rest of the organization, including underwriting, claims, insurance product, operations, finance, and marketing. The Data Scientist, Insurance role will build machine learning and AI models to deliver value to all these business units and more. We want to hire someone with a diverse methodological skill set, who enjoys digging into data and using it to solve business problems, whatever they may be. Because we are building the team, there is ample opportunity for creative freedom and flexibility.
A day in the life could include: 

Development of GLM and tree-based models to predict profitability of each insured.
Working with data engineering & business intelligence to develop modeling datasets, and contributing to the buildout of these data models
Build ensemble algorithms to predict customer retention & conversion
Automation of Kin’s direct mail strategy
Creation of a lifetime value model to prioritize marketing by person/property and marketing initiative
Researching advanced AI techniques to advance the industry, including building a computer vision model, and developing state of the art NLP models to interpret documents and assist in claims handling.
Ideating Machine Learning use cases with business partners; gathering requirements, testing feasibility, etc.

I’ve got the skills… but do I have the necessary ones?

Bachelor’s degree or Masters in Machine Learning, Statistics, Mathematics, Computer Science, Economics, or a related field
Masters / PhD in a technical field preferred
Experience developing GLMs & tree-based models
2-5 years working experience developing ML models
Insurance experience preferred
Experience interfacing with business partners to define data science projects and solutions
Must have experience in applied mathematics or statistics 
Experience in programming in Python and understanding of the software development life cycle
Excellent communication skills, both oral and written
Familiarity with natural language processing models a plus
Interest or experience in highly regulated and / or startup environment(s)
Passion for telling stories with data

Oh, and don’t worry, we’ve got you covered! 

Medical, Dental, Vision, Disability and Life Insurance
Flexible PTO policy 
Remote work
Generous equity package
401K with company match
Parental leave
Continuing education and professional development
The excitement of joining a high-growth Insurtech company and seeing your work make an impact
Principal Data Scientist at Trellis

About the role:
As the Principal Data Scientist at Trellis, you’ll lay the foundation for a world class data science team. You’ll use our troves of data to optimize the experiences we offer to consumers and help unlock the value of their insurance data. Ultimately, you’ll help turn our data into accurate predictions, strategic insights, and user value.
Tasks will include:

Building and managing a roadmap of valuable data science projects aligned with our strategy
Building prediction models from our wide array of data sources
Developing hypotheses and proposing experiments to improve our products
Owning data science projects from conception to deployment, in concert with our product, design, and engineering teams
Uncovering insights that drive business strategy and decision making

You should have:

4-5+ years of experience in data science, ideally in roles that deployed working models to production systems for consumer experiences
Track record of success leading initiatives that drove user value
Strong SQL skills
Fluent in R, Python, and/or other languages used in data science
Communication ability: polished written documents that explain complex concepts to internal stakeholders
Ownership mentality: willing to do whatever it takes to create value from your work
Experience in insurtech/fintech is a plus
Senior Data Scientist at Humana

Description
Growth Analytics & AI within Humana is dedicated to transforming members’ journeys and Humana’s services using technology and analytics. We are looking for a Senior Data Scientist who will design studies and utilize cutting-edge predictive modeling techniques, test rigorous hypotheses, and turn data and insights into actionable plans. Being part of a talented team of Data Scientists with broad skills and applications, the Senior Data Scientist will work cross-functionally and collaboratively with teams across the enterprise through innovative machine learning, R&D, and cutting-edge platforms. The scope of our work includes forecasting, predictive modeling, designing business experiments, and ROI studies. The ideal candidate will have hands-on experience with healthcare data, demonstrated
Read more about this job
Senior Nlp Data Scientist at Humana

Description
Humana is seeking a Senior Data Scientist who has strong experience with Natural Language Processing (NLP). The ideal candidate will have experience developing NLP models with transformer architecture and preferably have experience with Hugging Face. Additionally, the ideal candidate will have experience with topic modeling and/or sentiment analysis.
This is your opportunity to join our Fortune #40, Best Places to Work company and help us make a difference as we help our members achieve their best health!
Responsibilities
The Senior Data Scientist uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Senior Data
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Manager Data Science at Humana

Description
Humana’s Provider Payment Integrity organization is looking for an experienced Data Science Manager to join the Claims Cost Management (CCM) Solutions Support team working from home anywhere in the US. This dedicated team is focused on building data-driven analytical solutions to prevent fraudulent claims.
Responsibilities
The Data Science Manager within Provider Payment Integrity will utilize their leadership skills and improvement process experience to lead a remote team of 6 highly skilled associates that are located throughout the country. This team will consists of Data Scientist, Cognitive/Machine Learning Professionals and a Database Engineer. This Manager will be experienced and knowledgeable in mathematics, statistics, modeling, business analysis
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Data Scientist at Planet

About the Role:  
Planet is seeking an entrepreneurial Data Scientist to join our Data team. The team is responsible for bringing best-in-class data products to Planeteers as we look to achieve our North Star over the next decade and enable every Planeteer to measure the impact of their work towards our triple-bottom-line (planet, people, profit). This key contributor will play a critical role in shaping the team’s technical direction to guide Planet’s product, technology, and business teams. Core responsibilities will be focused on data mining, metric development, causal inference, and delivering quantitative insights to influence product & business strategy. 
Impact You’ll Own:

Drive the full data science lifecycle–from exploratory data mining, problem definition, experimental design and instrumentation to data conditioning, analysis, and storytelling–uncovering actionable insights on Planet’s customers, products, and platform in terabytes of data
Partner with cross-functional teams worldwide from Product, Engineering, and Design using data to better understand and optimize the customer experience
Catalyze innovation by translating business requirements into data products (e.g. automated KPI reporting, customer segmentation analyses, dynamic pricing models) that play a critical role in helping us build our Earth Data Platform

What You Bring:

2-3+ years of experience in data science supporting commercial or government software products
Excellent skills in problem formulation, metrics definition, ETL/ELT pipelines, statistical methods, and data visualization
Development background using Python, SQL, DBT, Git, and cloud-based platforms, like Google Cloud Platform or Amazon Web Services, to store and analyze data
Passion for Planet’s mission to use space to help life on Earth

What Makes You Stand Out:

Experience refactoring large (> TB), disparate, poor-quality datasets
Background writing production code or MLOps
Domain expertise in remote sensing, geospatial information systems, or product analytics
Professional examples where you used data to influence business decisions that generated customer value
History with world-class data teams working in a fast-paced, customer-centric culture
Demonstrated success collaborating across global time zones in a hybrid work environment
Proven record of problem solving and overcoming ambiguity with minimal direction
Ability to communicate effectively to technical and non-technical audiences
Desire to learn quickly
Curiosity, creativity, and collegiality!

Benefits While Working at Planet:

Additional company winter holidays and regular global days off
Remote friendly work environment and flexible working hours
Contribution to our growth by offering equity options for employees
Giving back to the community - one day per quarter for charitable work
Learning and Tuition Reimbursement
Regular hack-weeks and meetup events to exchange knowledge
Home office budget
Employee Resource Groups providing empowering spaces for connection and mentorship

#LI-NB1
#LI-REMOTE
Senior Data Science Manager Pricing Promotions at Shopify

You have:
Documented experience in pricing optimization and defining pricing strategy through advanced analytics and data science efforts.
Experience in driving customer growth through pricing optimization and experimentation. 
Been a leader in multiple tech companies where analytics on top of massive data sets drives product & business decisions.
Previously managed other managers and can oscillate your leadership style relative to the needs of individual contributors that are also on your team.
Exceptional problem solving and analysis skills combined with the ability to synthesize and effectively communicate findings to both technical and non-technical stakeholders.
A product mindset that enables you to get to the root of problems faced by customers and users and to create data solutions and products to solve these challenges.
It would be great if you have experience with:
Cloud platforms: Google Cloud Platform (GCP), AWS

Large-scale data-platform tools:
Data Storage and Access: HDFS, Presto
Data processing/integration: Kafka, Spark
Analytics Datastores: AWS Redshift, GCP BigQuery
Visualization: D3, Mode Analytics, Tableau
Programming languages: Python, Scala
SQL and debugging SQL queries



Analytical techniques:
Background in machine learning including experience implementing models at scale, including in the areas of price elasticity modeling and experimentation
Experimentation: A/B test design and analysis, quasi-experiments
Attribution-modeling
Forecasting


All your information will be kept confidential according to EEO guidelines.
We know that looking for a new role can be both exciting and time-consuming, and we truly appreciate your effort. And remember, we want to know what you’re really interested in building and why you want to build it at Shopify, so please give us as much detail on this as you’d like in the answers on the next page. 👍 📖
At Shopify, we understand that experience comes in many forms. We’re dedicated to adding new perspectives to the team - so if your experience is this close to what we’re looking for, please consider applying.

#LI-KO3 #LI-REMOTE #LI-AH1
Senior Data Scientist Revenue at Shopify

Data is a crucial part of Shopify’s mission to make commerce better for everyone. We organize and interpret petabytes of data to provide solutions for our merchants and stakeholders across the organization. From pipelines and schema design to machine learning products and decision support, data science at Shopify is a diverse role with many opportunities to positively impact our success.
Our Data Scientists focus on pushing products and the business forward, with a focus on solving important problems rather than specific tools. We are looking for talented data scientists to help us better understand our merchants and buyers so we can help them on their journey.
Responsibilities:
​​​​​​Proactively identify and champion projects that solve complex problems across multiple domains
Partner closely with product, engineering and other business leaders to influence product and program decisions with data
Apply complex analytics and/or ML techniques with a focus on sales performance optmization. 
Design and implement end-to-end data pipelines: work closely with stakeholders to build instrumentation and define dimensional models, tables or schemas  that support business processes
Build actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products
Influence leadership to drive more data-informed decisions
Define and advance best practices within data science and product teams
#LI-DNI
Senior Applied Scientist at Samsara

About the role:
The Samsara ML/CV team builds end-to-end machine learning and computer vision solutions for our customers as well as core ML infrastructure for Samsara. As a Senior Applied Scientist, you will be a tech leader and key contributor in building scalable ML infrastructure and tools. You will work closely with scientists as well as full-stack, firmware, and platform teams to deliver core infrastructure, services, and optimizations.
This role can be office-based or fully remote in the US and Canada.

In this role, you will: 


Build and improve the accuracy of ML / CV models, including retraining and optimizing open-source models to solve Samsara-specific problems 
Work with petabyte-scale data from Samsara camera and sensor devices to develop new models
Research, adapt, and apply cutting edge techniques in CV and deep learning
Optimize models for inference on the backend and/or on edge devices
Partner with our hardware teams to design devices for optimal performance and cost
Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices

Minimum requirements for the role:

BS or MS in Computer Science or other technical degree
4+ years experience as an Applied Scientist, Machine Learning Engineer, or similar role
Strong proficiency in one or more common languages (e.g., C++, Golang, Java, Python) 
Proficiency with common ML tools (e.g., Spark, TensorFlow, PyTorch)
Experience deploying and iteratively refining models using customer feedback loops
Comfortable with full-stack / backend development code to build a strong understanding of underlying data structures and other dependencies

An ideal candidate also has:

Ph.D. in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics)
Experience building, deploying, and optimizing ML models on the edge
Experience building computer vision features
Expertise optimizing distributed model training with GPUs
Senior Data Scientist Optimization at Edward Jones

Want a meaningful career where you can make a difference? Edward Jones sounds perfect for you.
Collaboration. Autonomy. Opportunity. Words our headquarters associates use when talking about working at Edward Jones. Words that describe what it’s like being part of a firm where everyone is aligned toward a singular focus: serving the client. And everyone is working to make the firm better together – as they grow as individuals. If these words resonate with you, we should talk.
Job Overview
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Position Schedule: Full-Time
If you thrive in a collaborative environment, have a learning mindset, and can communicate complex ideas in a straightforward way, this could be the role for you to make a real impact.
Join the Firm Analytics team and help us unlock the power of data science to solve a wide range of business challenges and improve the people-experience through data-driven capabilities and insights. As a Senior Data Scientist focused on optimization, you’ll work closely with business partners to learn about financial...
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