Leads strategy, development, and modernization of end-to-end modeling data pipelines and feature stores. Oversees data analysts, MLOps specialists, and subject matter experts while standardizing data ingestion, lineage, feature management, model calibration, and deployment. Partners across data science, technology, product, and business teams to deliver scalable AI and predictive analytics solutions, particularly for pricing models. Drives cross-functional change, develops talent, and provides strategic direction for modeling data practices.
Description
Leads the development and delivery of end-to-end data pipelines and feature store capabilities that give data scientists the modeling data they need, at the speed the P&L vertical teams require.
Provides strategic and tactical direction for the department, and helps set the direction for how MDS, data scientists, and deployment teams across US Date Science (USDS) work with modeling data. This position requires a proven ability to lead large-scale change across multiple teams.
Responsible for the management, technical oversight, and development of a team of data analysts, MLOps specialists, and subject matter experts. Owns the strategy and execution for modernizing and standardizing the modeling data lifecycle, from data ingestion through model deployment, in partnership with our P&L vertical data science, modeling data, and deployment teams.
Uses modern pipeline frameworks and scalable architecture patterns so data lineage is tracked throughout feature development. Leads the design and adoption of a feature store strategy that ensures features are defined once, managed consistently across model development, calibration, and deployment, and can be added to directly by data scientists. Leverages pipeline modernization to develop AI solutions that speed up how features are built, tested, and maintained.
Requires deep knowledge of modern data pipelines and feature management practices, including tools such as dbt, Snowflake, and Databricks, and advanced application of those practices to the development, calibration, and deployment of pricing models.
Collaborates with USDS, Data Office, DAE, ED&DS, and Product Delivery in developing these solutions.
Qualifications
About Us
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
$179,000.00 - 322,000.00
Leads the development and delivery of end-to-end data pipelines and feature store capabilities that give data scientists the modeling data they need, at the speed the P&L vertical teams require.
Provides strategic and tactical direction for the department, and helps set the direction for how MDS, data scientists, and deployment teams across US Date Science (USDS) work with modeling data. This position requires a proven ability to lead large-scale change across multiple teams.
Responsible for the management, technical oversight, and development of a team of data analysts, MLOps specialists, and subject matter experts. Owns the strategy and execution for modernizing and standardizing the modeling data lifecycle, from data ingestion through model deployment, in partnership with our P&L vertical data science, modeling data, and deployment teams.
Uses modern pipeline frameworks and scalable architecture patterns so data lineage is tracked throughout feature development. Leads the design and adoption of a feature store strategy that ensures features are defined once, managed consistently across model development, calibration, and deployment, and can be added to directly by data scientists. Leverages pipeline modernization to develop AI solutions that speed up how features are built, tested, and maintained.
Requires deep knowledge of modern data pipelines and feature management practices, including tools such as dbt, Snowflake, and Databricks, and advanced application of those practices to the development, calibration, and deployment of pricing models.
Collaborates with USDS, Data Office, DAE, ED&DS, and Product Delivery in developing these solutions.
Qualifications
- Advanced degree in Statistics, Mathematics, Data Science, Computer Science, or a related field preferred.
- Typically 8+ years of relevant experience, including leadership experience in data science, analytics, data operations, or MLOps.
- Experience sourcing, integrating, and governing data from enterprise data warehouses and external vendors
- Ability to partner with data science, technology, and business stakeholders and communicate clearly with technical and non-technical audiences
- Responsible for the management, technical oversight and development a team of data science and advanced analytics staff, which may include subordinate managers.
- Coaches team to understanding of organizational vision and goals.
- Collaborates with business partners to develop tools and services such as modeling, dashboard development, and decision aids to drive strategic decision making.
- Provides strategic and tactical direction at the highest levels. Has accountability for the performance and results of one or more large, strategically important business unit in an extremely large market.
- Works on issues of diverse scope where analysis of situation or data requires evaluation of a variety of factors, including an understanding of current business trends.
- Owns relationship with a defined segment of the business, delivering advanced tools and insights, including ongoing monitoring of metrics and initiatives.
- Responsible for highly technical, individualized and difficult to develop tools and their usage which are transformative in nature and have broad strategic impact to the aligned business units(s).
- Leads highly technical, complex, and cross functional projects that drive change across function, SBU or Corporate Department.
- Directs and may perform highly complex, technical and creative predictive analytics projects and cross functional assignments within designated business unit collaborating with multiple functions.
- Shapes the data science community and/or larger audiences and leads cross functional working groups.
About Us
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
$179,000.00 - 322,000.00
Similar Jobs at Liberty Mutual Insurance
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Leads strategy, architecture, governance, sourcing, and delivery of training and calibration data for data science and pricing teams. Oversees data engineering and pipeline modernization, vendor and warehouse integration, source-system changes, data lineage, and model-ready dataset delivery. Manages the Modeling Data Solutions organization, partners with enterprise data stakeholders, and guides teams supporting business-line data needs.
Top Skills:
Amazon SagemakerApache AirflowAWSDatabricksDbtSnowflake
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Analyzes complex regulatory data requests across insurance data sources, translates ambiguous guidance into precise requirements, collaborates cross-functionally, and delivers defensible findings. Builds reporting for leadership, documents data logic, and improves processes through automation, AI-assisted analysis, and reusable data practices. Leads projects independently and serves as a trusted expert in underwriting data and business processes.
Top Skills:
ClaudeGitGithub CopilotGptPythonSASSas ViyaSnowflakeSQL
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Handles inbound calls and warm leads, consults customers on insurance needs, recommends appropriate property and casualty coverage, and converts prospects into policyholders. The role includes paid training and licensing support, customer communication, sales closing, and brand representation. Employees must work a specified weekday and weekend schedule, maintain a compliant home workspace, and meet internet connectivity requirements.
Top Skills:
Cable InternetDslFiber InternetPcWired High-Speed Internet
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
