Director of Data Science – Employee Benefits

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.   

Are you ready to transform the future of insurance through enterprise-grade AI?

Join The Hartford’s AI Accelerator team as a Director of Data Science supporting our Employee Benefits business. This role is part of a high-impact, cross-functional team of data scientists, engineers, and domain experts focused on delivering scalable, agentic AI solutions that drive measurable business outcomes.

We are seeking a visionary leader with deep technical expertise and a passion for innovation to help shape the future of underwriting, claims, and customer experience in Employee Benefits. You will lead the development and deployment of advanced AI capabilities—from multimodal models and agentic workflows to real-time decision systems—while fostering a culture of experimentation, excellence, and enterprise collaboration.

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).

Key Responsibilities:

• Lead end-to-end development of AI solutions for Employee Benefits, from problem formulation to production deployment.
• Partner with business leaders, engineers, and subject matter experts to identify high-impact use cases and deliver measurable value.
• Architect and implement agentic workflows, LLM-based systems, and multimodal pipelines tailored to underwriting and claims processes.
• Drive the development of reusable AI components and evaluation frameworks aligned with enterprise standards.
• Mentor and grow a team of data scientists, fostering technical excellence and career development.
• Collaborate with the AI Enablement and Science Excellence teams to ensure solutions are scalable, secure, and aligned with enterprise strategy.
• Stay current with emerging AI technologies and evaluate their applicability to Employee Benefits.

Qualifications:

• Master’s or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or progress towards a relevant professional designation
• 8+ years of experience in applied AI, machine learning, or data science, with a focus on production-grade solutions.
• Experience with managing Data Scientists and providing guidance through model development
• Proven track record of leading cross-functional teams and delivering enterprise-scale AI solutions.
• Expertise in LLMs, GenAI, agentic architectures, and multimodal systems.
• Strong understanding of insurance workflows, especially in Employee Benefits, is a plus.
• Excellent communication and stakeholder management skills.
• Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution
• Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques

Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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