Liberty Mutual

Analyst, Data Science, Personal Lines Auto Modeling

Boston, MA
March 15, 2025
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Deadline date:

Job Description

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.

Description

The US Data Science (USDS) Personal Auto Modeling group is looking for talent to help drive pricing segmentation for Liberty’s lead line. We are expanding our team to increase sophistication and enable complex state solutions, with several openings for individual contributors to help build and implement our Usage Based Insurance (Telematics) and Core Auto Pricing models. This is a great opportunity to combine business acumen with predictive modeling expertise to influence every aspect of the product development process, from product design to model build and deployment.

This is a joint posting for multiple openings across both our Core Auto Pricing and Usage Based Insurance (Telematics) teams. Our USRM Data Science Personal Lines Auto Modeling group is seeking talented individual contributors to help develop pricing models, optimize and plan the delivery of those models, perform research, and bridge the gap between the technical decisions of model development and the practicalities of business implementation for Usage Based Insurance (Telematics) and/or Core Auto Pricing products. In these roles, analysts will closely collaborate with a high-functioning team of data scientists and insurance professionals to develop and implement our next generation of pricing models for either our Core Auto Pricing programs or our Telematics programs. Leverage your business acumen, project planning skills, intellectual curiosity, and technical proficiency through both collaborative and independent projects. Analysts will have the opportunity to influence every aspect of the product development process, from product design to model build and deployment, but will also have opportunities to collaborate on related projects with our internal partners.

Successful candidates will understand business goals and strategy, have experience with data sourcing and exploratory data analysis, and be familiar with the basics of statistical modeling. Solid communication and interpersonal skills are critical to the roles, as the individuals we hire will work very closely with their respective team and internal partners as we implement, monitor, and enhance our programs. These positions will play a key role in expanding the Core and Telematics auto pricing capabilities of the organization across the US.

**This is a ranged posting, level offered will be based on skills and experience at manager discretion.**

**This role may have in-office requirements depending on candidate location.**

In these roles, you can expect to:

  • Assist in the build of sophisticated pricing models for Liberty Mutual’s Personal Lines Auto programs.
  • Understand and articulate trade-offs between design choices.
  • Help coordinate the filing and implementation of our programs.
  • Understand and successfully respond to state department questions about our pricing models.
  • Undertake analytical research that will inform business decisions.
  • Develop solutions to business problems in the context of our broader Auto portfolio.
  • Test and implement novel features to better align rate to risk.
  • Learn to use rigorous modeling techniques to inform pricing decisions.
  • Regularly engage with the data science community and stay up to date with data science best practices.

Preferred skills and experience include:

  • Can correctly specify, build, interrogate, and interpret predictive models.
  • Prior experience in insurance, statistics, banking, finance or other regulated industries.
  • Familiarity with Python, R and/or SQL programming languages.

Qualifications

  • Solid knowledge of predictive analytics techniques and statistical diagnostics of models.
  • Advance knowledge of predictive toolset; expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Has a value-driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Master’s degree (scientific field of study) and 0-1 years of relevant experience or a Bachelor’s degree (scientific field of study) and 3+ years of relevant experience.

About Us

As a purpose-driven organization, Liberty Mutual is committed to fostering an environment where employees from all backgrounds can build long and meaningful careers. Through strong relationships, comprehensive benefits and continuous learning opportunities, we seek to create an environment where employees can succeed, both professionally and personally.

At Liberty Mutual, we believe progress happens when people feel secure. By providing protection for the unexpected and delivering it with care, we help people embrace today and confidently pursue tomorrow.

We are proud to support a diverse, equitable and inclusive workplace, where all employees feel a sense of community, belonging and can do their best work. Our seven Employee Resource Groups (ERGs) offer a centralized, open space to bring employees and allies together to connect, learn and engage.

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://LMI.co/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.

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