Analyst II, 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. 

The USRM Claims Data Science team is hiring an Analyst II, Data Science, as part of a broader expansion of our team. This role will focus on supporting the Auto Physical Damage claims organization.

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!

As an Analyst II, Data Science, you will collaborate with business partners to develop predictive models that enable dynamic software systems and data-driven strategic decision-making. This role utilizes data science techniques to manipulate large structured and unstructured data sets, identify patterns in raw data, and develop models to predict the likelihood of a future outcome and/or to optimize business solutions.

This level reflects solid knowledge of predictive analytics techniques, while continuing to learn how to apply techniques to business issues.

**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:

• Collaborates with claims process, experience, technology, and analytics teams to help create the most accurate, caring, and efficient claims organization in the insurance industry.
• Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions.
• Follows ML Ops best practices to create organized code repos, production-quality code, and reproducible results.  
• Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business application.    
• Translates quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data.     
• Enables the business to make clear trade-offs between and among choices, with a reasonable view into likely outcomes.    
• Customizes analytic solutions to specific client needs.  
• Regularly engages with the data science community and participates in cross-functional working groups.

• Solid knowledge of predictive analytics techniques and statistical diagnostics of models.
• Foundational/intermediate 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 Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience, a Master`s degree (scientific field of study) and 2 to 3 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 4+ years of relevant experience.