Analyst, Data Science, Earnix Design

Are you passionate about pricing in the Insurance Industry? Would you like to join a dedicated team responsible for deploying pricing programs across all our retail lines in United States? Then this is your next job!

The US Data Science (USDS) Earnix Design Excellence and Support team is looking for an Analyst I/Analyst II/Asst. Director, Data Science, to design and build major pricing programs in Earnix and develop best-in-class practices for pricing deployment design. The Earnix initiative is transforming our pricing ecosystem and post modeling processes to increase speed to market and deploy more sophisticated models across all lines of business. This role will develop deep expertise in deploying, maintaining, and monitoring Liberty Mutual's pricing models, collaborating heavily with data science, product delivery, and tech teams. It will also play a key role in establishing new Earnix capabilities to scale the speed and efficiency of implementing pricing programs and other use cases.

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

**This role may have in-office requirements dependent upon candidate location.**

Job Responsibilities

• Design best-in-class capabilities to support post-modeling activities, including calibration, dislocation, and filing.
• Build USDS pricing programs in Earnix.
• Design and implement other use cases of Earnix as a rating engine.
• Ensure accuracy of all pricing and non-pricing outputs from Earnix.
• Design and maintain rigorous data models for Earnix analytical projects and API.
• As required, troubleshoot and support post launch queries and issues.
• Improve and automate processes where applicable.
• Engage with the data science community and participates in cross-functional working groups.

This role may be for you if you:

• Love insurance rating programs and want to get a deeper understanding of how they work.
• Frequently bring voices together to find patterns in business problems.
• Are comfortable challenging the status quo to make systems simpler, more robust, and scalable.
• Enjoy documenting and sharing best practices to accelerate the whole team.
• Get excited by delivering business critical, production-ready products.

Ideal candidate will have:

• Background in insurance pricing.
• Strong programming skills in Python and R.
• Working familiarity with GLMs and GBMs for predictive modeling.
• Strong feature engineering and transformation skills.
• Applied use of multi-level or ensemble modeling techniques.
• Experience creating rating logic and implementing rating programs in tools like Earnix, Radar Live, etc.