Director, Data Science

Manage and develop a team of data science and advanced analytics staff, driving accurate risk classification in pricing across three lines of business. Apply broad knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions. Drive innovation in the application and development of tools and practices. Mine large data sets using sophisticated analytical techniques to generate insights and inform business decisions. Identify and tests hypotheses, ensuring statistical significance, and build highly complex, technical and creative predictive analytics for business applications. Translate quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data. Enable the business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes. Guide aspects of project design as a technical consultant for the team. Customizes analytic solutions to specific stakeholder needs. Regularly engage with the data science community and leads cross functional working groups. Position requires domestic (U.S.) travel up to 5% Telecommuting permitted up to 100%, Lead and develop team members including hiring, mentorship, individualized development planning, performance management, code and research review, and guidance on model design and tool selection. Project and stakeholder management including scope and prioritize work, estimate effort, assign resources, balance planned versus ad-hoc requests, evaluate new requests, negotiate timelines and replan deliverables. Cross-functional partnership and influence including work with product-line, state management, underwriting, IT and compliance and build business cases, advocate the pricing roadmap and support multi-state implementation and adoption. Governance and quality controls including maintaining audit-ready documentation, reproducible code, validation artifacts and versioning; ensure regulatory, privacy, fairness and transparency compliance; and promote testing, peer review, and continuous improvement. Experience may be gained during graduate program. Will accept any suitable combination of education, training, and/or experience. Multiple Positions Available. REFER TO: To apply, please visit https://jobs.libertymutualgroup.com/, select “Search Jobs,” enter job requisition #2026-XXXXX 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.

About Us

Duties: Manage and develop a team of data science and advanced analytics staff, driving accurate risk classification in pricing across three lines of business. Apply broad knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions. Drive innovation in the application and development of tools and practices. Mine large data sets using sophisticated analytical techniques to generate insights and inform business decisions. Identify and tests hypotheses, ensuring statistical significance, and build highly complex, technical and creative predictive analytics for business applications. Translate quantitative analyses and findings into accessible visuals for non-technical audiences, providing a clear view into interpreting the data. Enable the business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes. Guide aspects of project design as a technical consultant for the team. Customizes analytic solutions to specific stakeholder needs. Regularly engage with the data science community and leads cross functional working groups. Position requires domestic (U.S.) travel up to 5% Telecommuting permitted up to 100%

Employer will accept a Bachelor’s degree (or foreign equivalent) in Actuarial Science, Statistics or related field and 10 years of experience in the job offered or in a Director II, Data Science-related occupation. Position requires demonstrable experience with the following: P&C insurance domain expertise includes deep knowledge of exposure, premium and loss data, classification plans, state- and plan-level rate setting, and actuarial principles including credibility, loss development, trend analysis, experience rating and ratemaking. Develop, validate and deploy pricing models including GLMs and gradient-boosted models and diagnose model performance across lines of business and products Own the full modeling lifecycle including data procurement, feature engineering, model selection, cross-validation, back-testing, calibration, monitoring, and model retraining. Technical proficiency with modeling tools and languages, requiring experience in at least two tools, including Python or Emblem, and additional proficiency in at least one of SAS or R. Experience with large-scale data wrangling and evaluation and selection of appropriate internal toolsets. Measure and improve pricing effectiveness including quantifying current pricing, identifying gaps, recommending pricing and model changes, define KPIs tied to underwriting profitability, and perform cost-benefit analyses to inform business decisions. Lead and develop team members including hiring, mentorship, individualized development planning, performance management, code and research review, and guidance on model design and tool selection. Project and stakeholder management including scope and prioritize work, estimate effort, assign resources, balance planned versus ad-hoc requests, evaluate new requests, negotiate timelines and replan deliverables. Cross-functional partnership and influence including work with product-line, state management, underwriting, IT and compliance and build business cases, advocate the pricing roadmap and support multi-state implementation and adoption. Governance and quality controls including maintaining audit-ready documentation, reproducible code, validation artifacts and versioning; ensure regulatory, privacy, fairness and transparency compliance; and promote testing, peer review, and continuous improvement. Experience may be gained during graduate program. Will accept any suitable combination of education, training, and/or experience. Multiple Positions Available., Employer will accept a Bachelor’s degree (or foreign equivalent) in Actuarial Science, Statistics or related field and 10 years of experience in the job offered or in a Director II, Data Science-related occupation. Position requires demonstrable experience with the following: P&C insurance domain expertise includes deep knowledge of exposure, premium and loss data, classification plans, state- and plan-level rate setting, and actuarial principles including credibility, loss development, trend analysis, experience rating and ratemaking. Develop, validate and deploy pricing models including GLMs and gradient-boosted models and diagnose model performance across lines of business and products Own the full modeling lifecycle including data procurement, feature engineering, model selection, cross-validation, back-testing, calibration, monitoring, and model retraining. Technical proficiency with modeling tools and languages, requiring experience in at least two tools, including Python or Emblem, and additional proficiency in at least one of SAS or R. Experience with large-scale data wrangling and evaluation and selection of appropriate internal toolsets. Measure and improve pricing effectiveness including quantifying current pricing, identifying gaps, recommending pricing and model changes, define KPIs tied to underwriting profitability, and perform cost-benefit analyses to inform business decisions.