Analyst II, Data Science

• Applies knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform underwriting decisions.
• Research and develop in-house AI/ML products with other team members, including data scientists, IT developers, and business stakeholders.
• Identifies and tests hypotheses, ensuring statistical significance, as part of building and developing predictive models for business applications.
• Understand our underwriting process and principles, determine predictive modeling strategies to improve insurance risk selection and pricing.
• 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.
• Responsible for smaller components of projects of moderate-to-high complexity.
• Regularly engages with the data science community and participates in cross-functional working groups.

Domestic travel required up to 10%.

Telecommuting permitted up to 60%.

Requirements: 

Employer will accept a PhD (or foreign equivalent) in Statistics, Data Science or related field and 1 year of experience in the job offered or in an Analyst II, Data Science-related occupation.

Position requires demonstrable experience in the following, which can be gained in a professional or academic setting:

• Demonstrated proven, in-depth knowledge of deep learning, machine learning, predictive analytics, and statistical modeling, including model diagnostics and validation.
• Demonstrated comprehensive knowledge of data science toolkit, encompassing data warehousing, data mining, and advanced data analysis techniques.
• Extensive hands-on experience with statistical programming languages including Python, SQL and R.
• Deep understanding and practical application of MLOps best practices for efficient model development, deployment, and monitoring.
• Demonstrated hands-on experience of using MLFlow, Databricks, and Docker Containers.
• Demonstrated comprehensive knowledge of insurance operations and familiarity with procedures of finance, underwriting, insurance claims and information technology.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely, both verbally and in writing.
• Demonstrated a strong understanding of the work context and the impact of data science on insurance products.

Domestic travel required up to 10%.

Telecommuting permitted up to 60%

To apply, please visit https://jobs.libertymutualgroup.com/, select “Search Jobs,” enter job requisition #2026-74318 in the “Job ID or Keywords” field, and submit resume. Alternatively, you may apply by submitting a resume via e-mail to RecruitLM@LibertyMutual.com. Reference requisition number in subject of e-mail.