Director, Data Science - Rollout acceleration AI

AI has the potential to transform how insurers bring new products to market. Help us make sure it does. US Data Science (USDS) is building a new team that will use advanced AI to bring our pricing programs to market faster, and we are hiring three senior data scientists to help launch it. The team will build state-of-the-art evaluations for AI and agentic systems. Those evaluations tell us how much value the AI delivers, how accurate it is, and what the risk is when it gets something wrong, so we can move high-value applications into production with confidence. This is a new, highly visible team, and its work will shape how AI is used in the core pricing work of US Retail Markets (USRM). Each of the three roles reports into the Rollout AI team in USDS and has a dotted-line relationship with one of our lines of business: Property & Specialty, Auto, or Small Commercial. You will be the data science partner for your line of business while working as one team with the other two, sharing methods and tools. These roles will be filled at the Assistant Director or Director I level, depending on experience and skills.

**Level of position offered will be based on skills and experience at manager discretion**

This role may have in-office requirements depending on candidate location

**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel.**

Responsibilities: 

• Partner with your line of business's pricing, delivery, and technology teams to find where AI can speed up pricing program rollout.
• Build state-of-the-art evaluations for AI and agentic applications. Define accuracy metrics and ground truth, generate statistical tests and edge cases, and design experiments, including tests in production.
• Measure the value and risk of AI applications, including effort reduced, errors avoided, and time to market gained.
• Bring pricing expertise and product sense to AI projects, translating business needs into requirements and evaluation criteria.
• Prototype and build evaluation tooling and, over time, AI applications that accelerate rollout.

The ideal candidate will have: 

• Hands-on experience building and deploying insurance pricing models.
• Strong expertise in model evaluation, statistics, and experimental design.
• Strong coding skills (for example, Python) and a track record of building and shipping data science solutions.
• Strong, recent hands-on experience with modern LLMs, including but not limited to agentic coding, building LLMs into applications, and/or RAG.
• Experience evaluating generative AI or agentic systems is a plus.
• Strong communication and stakeholder skills, comfortable working across business, delivery, and technology teams.
• Resilient, curious, acts in service of the best answer, holds themselves to a high standard and wants to be around others who do the same.

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
• Ability to establish and build relationships within and outside the organization.
• Ability to give effective training and presentations to management and other groups.
• Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
• Broad knowledge of business drivers and market context.
• 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 a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of  8 years of relevant experience.