Data Science Team Lead Jobs
Data Science Team Lead jobs are open across technology, finance, healthcare, and retail, at every level from senior data scientist to director, with specializations in machine learning engineering, analytics leadership, and applied AI. Scan the live roles below and apply to whichever ones fit.
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Our Medical, Special Investigations, and Programs (MSP) Claims Data Science team is hiring a Director, Data Science to support growing business demand in Medical and Workers’ Compensation Claims. This is a senior individual contributor role for an experienced, execution-focused data scientist who can independently partner with stakeholders to identify, prioritize, and build ML and AI capabilities in a space with a minimal existing data science footprint.
A successful candidate in this role will partner closely with leaders in Claims and delivery partners in Insights & Solutions and Technology to establish and execute on a roadmap of foundational Machine Learning and AI capabilities to enhance adjuster workflows and related supporting processes (e.g., Quality Improvement). While this role will begin as an Individual Contributor, it is expected that this leader will build a team around them as they establish their execution strategy.
This role may have in-office requirements depending on candidate location
**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel.**
What you’ll do:
- Partner closely with leaders in Claims and other delivery partners (Insights & Solutions, Technology, and Enterprise Data) to identify AI/ML opportunities and create a delivery roadmap that prioritizes the most impactful work.
- Design, build, and iterate on Machine Learning and Generative & Agentic AI capabilities which deliver real business value for adjusters in Medical and Workers’ Compensation claims.
- Collaborate with our partner teams to architect & deliver end-to-end intelligent systems integrating machine learning, LLMs, RAG pipelines, agentic workflows, and structured/unstructured claims data to solve real business problems.
- Apply strong software engineering and ML/AI Ops practices, including object-oriented Python, modular design, test-driven development, and model monitoring.
- Define and implement evaluation and measurement strategies, including impact & acceptance KPIs, human-in-the-loop review, and automated quality metrics.
- Collaborate with Engineers, Product, Architecture, UX, and Claims stakeholders to translate ambiguous problems into working solutions.
- Provide technical mentorship and thought leadership through design reviews and collaboration.
Skills and Experiences:
- Expert-level machine learning & statistical modeling practitioner with track record for delivering measurable business value.
- Deep knowledge of insurance claims processes, especially in Workers’ Compensation or other medical-driven lines of business (e.g., Medical & Casualty, Disability).
- Experienced in Python development with object-oriented design and engineering best practices.
- Demonstrated AI/ML Ops experience including model lifecycle management, experimentation, evaluation, monitoring, and operational readiness in a cloud-native enterprise environment.
- Demonstrated ability to measure AI/ML and GenAI system quality and business impact using quantitative and qualitative approaches.
- Experience partnering with technical and business stakeholders in complex, enterprise environments.
Additional Skills and Experiences (Nice to Have):
- Experience delivering ML and AI products through Python API and Application frameworks like FastAPI and Streamlit (or equivalent)
- Demonstrated experience delivering business value with Generative & Agentic AI in an enterprise setting
- Building, deploying, and maintaining AI products using leading frontier models from providers like OpenAI, Anthropic, and Google
- Experience building generative & agentic AI solutions using frameworks like LlamaIndex, LangChain, LangGraph, or equivalent
- Exposure to CrewAI, AgentCore, or other agentic orchestration frameworks
- Familiarity with vector databases and embedding-based retrieval systems
- Deep knowledge of predictive analytic techniques and statistical diagnostics of models.
- Expert knowledge of predictive toolset. Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
- Ability to establish and build relationships within and outside the organization.
- Ability to give effective training and presentations to management, executives and other groups.
- Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
- Deep knowledge of business drivers and market context. Has a value driven perspective with regard to understanding of work context and impact.
- Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 5 years of relevant experience, a Master`s degree (scientific field of study) and 8 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and 12 years of relevant experience.
Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.
At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.
We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://www.libertymutualgroup.com/about-lm/careers/benefits
Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.
Fair Chance Notices
- California
- Los Angeles Incorporated
- Los Angeles Unincorporated
- Philadelphia
- San Francisco
Our Medical, Special Investigations, and Programs (MSP) Claims Data Science team is hiring a Director, Data Science to support growing business demand in Medical and Workers’ Compensation Claims. This is a senior individual contributor role for an experienced, execution-focused data scientist who can independently partner with stakeholders to identify, prioritize, and build ML and AI capabilities in a space with a minimal existing data science footprint.
A successful candidate in this role will partner closely with leaders in Claims and delivery partners in Insights & Solutions and Technology to establish and execute on a roadmap of foundational Machine Learning and AI capabilities to enhance adjuster workflows and related supporting processes (e.g., Quality Improvement). While this role will begin as an Individual Contributor, it is expected that this leader will build a team around them as they establish their execution strategy.
This role may have in-office requirements depending on candidate location
**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel.**
What you’ll do:
- Partner closely with leaders in Claims and other delivery partners (Insights & Solutions, Technology, and Enterprise Data) to identify AI/ML opportunities and create a delivery roadmap that prioritizes the most impactful work.
- Design, build, and iterate on Machine Learning and Generative & Agentic AI capabilities which deliver real business value for adjusters in Medical and Workers’ Compensation claims.
- Collaborate with our partner teams to architect & deliver end-to-end intelligent systems integrating machine learning, LLMs, RAG pipelines, agentic workflows, and structured/unstructured claims data to solve real business problems.
- Apply strong software engineering and ML/AI Ops practices, including object-oriented Python, modular design, test-driven development, and model monitoring.
- Define and implement evaluation and measurement strategies, including impact & acceptance KPIs, human-in-the-loop review, and automated quality metrics.
- Collaborate with Engineers, Product, Architecture, UX, and Claims stakeholders to translate ambiguous problems into working solutions.
- Provide technical mentorship and thought leadership through design reviews and collaboration.
Skills and Experiences:
- Expert-level machine learning & statistical modeling practitioner with track record for delivering measurable business value.
- Deep knowledge of insurance claims processes, especially in Workers’ Compensation or other medical-driven lines of business (e.g., Medical & Casualty, Disability).
- Experienced in Python development with object-oriented design and engineering best practices.
- Demonstrated AI/ML Ops experience including model lifecycle management, experimentation, evaluation, monitoring, and operational readiness in a cloud-native enterprise environment.
- Demonstrated ability to measure AI/ML and GenAI system quality and business impact using quantitative and qualitative approaches.
- Experience partnering with technical and business stakeholders in complex, enterprise environments.
Additional Skills and Experiences (Nice to Have):
- Experience delivering ML and AI products through Python API and Application frameworks like FastAPI and Streamlit (or equivalent)
- Demonstrated experience delivering business value with Generative & Agentic AI in an enterprise setting
- Building, deploying, and maintaining AI products using leading frontier models from providers like OpenAI, Anthropic, and Google
- Experience building generative & agentic AI solutions using frameworks like LlamaIndex, LangChain, LangGraph, or equivalent
- Exposure to CrewAI, AgentCore, or other agentic orchestration frameworks
- Familiarity with vector databases and embedding-based retrieval systems
- Deep knowledge of predictive analytic techniques and statistical diagnostics of models.
- Expert knowledge of predictive toolset. Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
- Ability to establish and build relationships within and outside the organization.
- Ability to give effective training and presentations to management, executives and other groups.
- Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
- Deep knowledge of business drivers and market context. Has a value driven perspective with regard to understanding of work context and impact.
- Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 5 years of relevant experience, a Master`s degree (scientific field of study) and 8 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and 12 years of relevant experience.
Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.
At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.
We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://www.libertymutualgroup.com/about-lm/careers/benefits
Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.
Fair Chance Notices
- California
- Los Angeles Incorporated
- Los Angeles Unincorporated
- Philadelphia
- San Francisco
Data Science Team Lead Jobs by Experience Level
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Find Data Science Team Lead JobsData Science Team Lead Job Market
Who's Hiring
What Employers Look For
The qualifications that appear most often in data science team lead jobs.
- 5+ years in data science with at least 2 years managing or leading a team
- Proficiency in Python and SQL for modeling, analysis, and pipeline work
- Experience delivering machine learning models into production environments
- Ability to translate business problems into data science project roadmaps
- Familiarity with cloud platforms such as AWS, GCP, or Azure
- Strong communication skills for presenting findings to non-technical stakeholders
Tips for Your Data Science Team Lead Job Search
Quantify your team leadership impact
Hiring managers want to see headcount managed, not just technical output. Rewrite your resume bullets to show how many data scientists or analysts you led, what delivery cadence you owned, and how your team's work tied to a measurable business outcome.
Show both IC depth and leadership breadth
Data science team lead roles screen out candidates who lean too far in either direction. Your resume needs concrete modeling or ML work alongside evidence of mentoring, roadmap ownership, or cross-functional collaboration, so reviewers see you can still do the technical work and run a team.
Apply early to roles that fit
Migrate Mate lists data science team lead openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target job descriptions that match your stack
Filter openings by the tools named in the description, whether that is Python, Spark, dbt, or a specific cloud platform. Applying to roles where your stack overlaps reduces screening attrition and signals immediate productivity to hiring teams.
Prepare a team narrative for the first interview
Most data science team lead screens open with a question about how you've structured or grown a data team. Prepare a two-minute answer that covers team composition, how you set technical direction, and one situation where you had to reprioritize the roadmap under pressure.
Negotiate scope before negotiating compensation
Before accepting or countering an offer, clarify what the team looks like on day one, whether headcount is approved or still planned, and who owns the data infrastructure. These details change the actual scope of the role and affect whether the compensation is appropriate.
Data Science Team Lead Jobs: Frequently Asked Questions
Which companies are hiring the most data science team leads?
The most active employers for data science team leads right now are TikTok, Agnik, and Wellington Management, and the most openings are in California, Washington, and Massachusetts, based on current listings on Migrate Mate as of November 2026. Demand is strongest at companies with established data platforms and product-led growth models.
How many data science team lead jobs are remote?
About 33% of data science team lead openings are fully remote or hybrid as of November 2026, reflecting strong employer flexibility for this seniority level. Roles focused on applied ML research and analytics strategy tend to be the most remote-friendly, while positions tied to embedded product teams often require some in-office presence.
How do you become a data science team lead?
Start by building a strong individual contributor foundation in data science, then actively seek opportunities to mentor junior teammates, own a project end-to-end, and present findings to stakeholders. Taking on informal tech lead or project lead responsibilities before the title change makes the transition much smoother and signals readiness to hiring managers.
Can you get a data science team lead role with limited leadership experience?
Yes, especially if you can point to informal leadership you've already done. Candidates who have mentored colleagues, led a cross-functional data initiative, or owned a production model from scoping through deployment can make a credible case. Framing your experience around outcomes you drove for a team, rather than just your individual technical work, is what moves you forward in screening.
What does the data science team lead interview process look like?
Most processes run three to four stages: an initial screen with a recruiter or hiring manager, a technical assessment covering modeling concepts or a take-home case study, a leadership interview focused on team management and cross-functional collaboration, and a final round with senior leadership or a panel. Some companies add a presentation where you walk through a past project and defend your decisions.
Where can I find and apply to data science team lead jobs?
You can find and apply to data science team lead jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that match your experience and preferred location or remote setup, and apply directly to each listing that fits.
See All 6 Data Science Team Lead Jobs
Find roles that match your experience and apply in just a few clicks.
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