Assistant Director, Data Science (STP)

Description

This a range posting. Candidates will be considered for the appropriate level depending upon experience and qualifications.

At Liberty Mutual, the Insights & Solutions group uses data, analytics, and technology to deliver innovative solutions that drive our US Retail Markets business forward. Within it, the Claims Data Science team focuses on developing sophisticated AI/ML driven solutions to help create the most accurate, caring, and efficient claims organization in the insurance industry.

The US Retail Markets Data Science team brings together a diverse range of talent to predict future risk and what our customers will need to recover. Our data engineers write code that turns trillions of bits of information into structured data-data that our hundred-plus Data Scientists analyze with cutting-edge modeling techniques to unlock insights. From there, our tools and deployment teams ensure this data can be practically applied to business problems across US Retail Markets. Join us and be a part of this dynamic group driving industry-leading data segmentation, fueling the team's success now and into the future.

Claims data science is bursting with opportunity. Recent advances in Large Language Models, Computer Vision, and other technologies bring many previously impracticable business challenges into the realm of possibility for data scientists. Claims data science can be a key competitive advantage for Liberty Mutual in the years to come; help us build that competitive advantage!

The US Retail Markets Claims Data Science team is hiring three Assistant Director and/or Director, Data Science positions as part of a broader expansion of our team. These are individual contributor positions, two roles will focus on Casualty claims, and one will focus on Property claims.

This role may have in-office requirements based on candidate location

Level of position offered will be based on skills and experience at manager discretion

Responsibilities:

• Apply knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.
• Lead end-to-end development of new predictive models for high-impact business outcomes (e.g., improving claims handling efficiency): frame and test hypotheses, design statistically rigorous experiments, assemble/label training data, engineer features, and train/validate models.
• Build state-of-the-art ML systems that leverage structured data, unstructured text, and generative AI; select and implement appropriate algorithms and evaluation methods to deliver measurable accuracy and business value.
• Follow ML Ops best practices to create organized code repos, production-quality code, and reproducible results.
• Stay up-to-date with the latest advancements in data science and machine learning, and apply them to solving complex problems in the insurance claims domain.
• Provide technical mentorship and guidance to junior data scientists.
• Responsible for larger components of projects of moderate to high complexity.
• Communicate findings through technical presentations, reports, and recommendations to both technical and non-technical stakeholders.
• Participate in cross-functional working groups and contribute to the broader data science community to promote best practices.

Preferred skills and experience:

• Broad conceptual understanding and practical knowledge of the end-to-end data science lifecycle.
• Exceptional hands-on data science technical skills (e.g. SQL, Python, and Statistical Inference).
• Experience collaborating with non-technical stakeholders to understand which problems need solving, design solutions, and bring them to market.
• Experience working with complex Type II data to assemble training datasets to appropriately model operational processes.
• Proficiency in Python and MLOps practices, with experience in version control (Git), code review, collaborative development workflows (e.g., GitHub/GitLab), and model versioning/experiment tracking (e.g., MLflow).

Additional skills and experiences that are nice to have:

• Knowledge of claims handling processes and experience working with claims data.
• Experience developing LLM-based solutions for production use cases.
• Practical experience with cloud platforms like AWS (preferably), Google Cloud, or Azure.
• Familiarity with data pipeline and workflow management tools like Airflow, among others.

Qualifications

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Expert knowledge of predictive toolset; reflects as expert resource for tool development.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
• Networks with key contacts outside own area of expertise.
• Ability to establish and build relationships within the aligned functional area or SBU.
• Ability to give effective training and presentations to peers, management and less senior business leaders.
• Ability to use results of analysis to persuade team or department management to a particular course of action.
• 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 2 years of relevant experience, a Masters degree (scientific field of study) and 4 years of relevant experience or may be acquired through a Bachelors degree (scientific field of study) and 5+ years of relevant experience.

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.

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 dedicated to fostering an inclusive environment where employees from all backgrounds can build long and meaningful careers. By actively seeking employee feedback and amplifying the voices of our seven Employee Resource Groups (ERGs), which are open to all, we create an environment where every individual can make a meaningful impact so we continue to meet the evolving needs of our customers.

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.

Fair Chance Notices

• California
• Los Angeles Incorporated
• Los Angeles Unincorporated
• Philadelphia
• San Francisco

Client-provided location(s): Boston, MA, Seattle, WA, Flexible / Remote

Job ID: liberty_mutual-2025-72497-en_2

Employment Type: OTHER

Posted: 2025-10-08T20:19:33