Director, Data Science Product Design & Modeling
At Liberty Mutual, our purpose is to help people embrace today and confidently pursue tomorrow. That's why we provide an environment focused on openness, inclusion, trust and respect. Here, you'll discover our expansive range of roles, and a workplace where we aim to help turn your passion into a rewarding profession.
Liberty Mutual has proudly been recognized as a Great Place to Work by Great Place to Work® US for the past several years. We were also selected as one of the 100 Best Places to Work in IT onIDG's Insider Pro and Computerworld's 2020 list. For many years running, we have been named by Forbes as one of America's Best Employers for Women and one of America's Best Employers for New Graduatesas well as one of America's Best Employers for Diversity. To learn more about our commitment to diversity and inclusion please visit: https://jobs.libertymutualgroup.com/diversity-inclusion
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.
The Product Design and Modeling team has an opening for a Director II, Data Science position that will drive pricing and non-pricing sophistication in the US Design team and will lead a team of 35 direct reports, potentially in multiple locations. The role will report directly to the Auto Design Lead but also have opportunities to work on projects across personal and business lines as well as globally in partnership with the East & West Design team.
- Drive research and innovation in modeling and data science techniques to improve our accuracy, efficiency, and speed to market
- Develop a team of best-in-class modelers
- Develop expertise in the US Personal Lines Auto product
- Lead the build of complex loss cost models across Auto Products, as well as Adjacent products (e.g., Property/Specialty, Business Lines, Pay As You Drive Products)
- Lead the build of complex non-pricing models (e.g., models to identify customers for non-renewal, models to estimate exposure, models to impute data)
- Explore and utilize advanced modeling techniques (e.g., machine learning techniques such as Elastic Nets)
- Work with massive amounts of data (e.g., 200 million records for our Liberty-brand Auto product) to build sophisticated models
- Collaborate with Pricing Program Managers and Delivery teams to help implement new pricing programs into market every 12 to 24 months
- Bachelor's degree required. Insurance designations such as FCAS or advanced degree in a quantitative field desirable.
- Overall 5-7 years of progressively more responsible experience, including supervisory experience.
- Strong analytical skills with solid understanding of all casualty actuarial techniques, standards, and assumptions. Expert skills in Excel, PowerPoint, and statistical software packages (e.g., SAS, Emblem) highly desired.
- Strong knowledge of insurance principles, underwriting and ratemaking concepts and the procedures of Underwriting, Distribution, Claims, Information Technology, Legal, and Finance departments
- High-level knowledge of data sources, tools, and the business (lines, systems, pricing plans), predictive modeling (GLM, GBM, Elastic Net), and code (e.g. SAS, SQL) preferred.
- Demonstrated ability to exchange ideas and convey complex information clearly and concisely, both verbally and in writing.
- Ability to establish and build effective relationships within and outside the organization.
- Ability to give effective training and presentations to senior management and other groups.
- Ability to lead and get work done through others. Ability to coach and develop staff members.