Analyst, Data Science

Join Demand and Decision Science to lead cutting-edge modeling efforts that shape pricing segmentation, customer retention and strategic business decisions for US Personal Lines. You’ll combine technical expertise with business insight, delivering actionable recommendations and innovative solutions that drive organizational success.

The USRM Demand & Decision Science Tactical Pricing team is seeking an independent, creative, and self-motivated individual contributor (Analyst, Data Science) to work on the US Personal Property & Specialty line of business. In this role, you'll be part of a newly formed team responsible for using machine learning techniques to proactively identify pricing segmentation opportunities across business segments. You'll help build out semi-automated modeling processes and pipelines on metrics such as conversion, win rate, and frequency residuals to help evaluate the performance of our pricing programs from a multi-variate perspective. You'll also build out model artifacts and standardized visuals to help interpret the results of these models. You'll work cross-functionally with State, Product, Risk Analytics, and other teams within USDS to help support tactical pricing decisioning and implementation.

**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:

• Applies various techniques including GLMs, machine learning, and causal inference techniques; Gains confidence in skill application using analytics and data science techniques to help build complex retention, conversion, and price elasticity models
• Establish modeling pipelines and standardized visuals to help support the identification, evaluation and decision-making process surrounding tactical pricing opportunities.
• Support the implementation of tactical pricing changes, gaining business experience with robust consultation and collaboration across the org regarding state-specific opportunities.
• Gains experience in enabling the business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes.
• Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.
• Generate data-driven answers to open-ended strategic questions related to tactical pricing and present out on recommendations to leadership.
• Regularly engages with the data science community and participates in cross-functional working groups.

The creative problem-solvers in Liberty Mutual’s Insights & Solutions group harness the power of data, analytics and technology to develop innovative solutions that drive our US Retail Markets business forward and support a high-performing culture. This group brings together highly talented thinkers and doers ready to challenge the status quo and make an impact. As a member of this cross-functional group, you’ll collaborate with teams across Liberty Mutual to deliver analysis that unlocks insights and sparks new, better ways of working.

The Insights & Solutions team provides critical analysis through five functional groups within US Retail Markets:
• Distribution, Marketing & Experience Insights & Solutions
• Data Office
• Claims & Service, Insights & Solutions
• Knowledge & Development Solutions
• Data Science

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.

• Data extraction and manipulation skills, EDA, transformations, and general linear models (GLM); preferred skills of basic CART and GLM.
• Foundational knowledge of predictive analytics tools.
• 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 (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience or may be acquired through a Bachelor`s degree and 3+ years of relevant experience.