Director of Data Science

The Hartford•Hartford, CT

1d•$153,200 - $229,800•Hybrid

About The Position

The Hartford is seeking a Director of Data Science to lead the Personal Insurance modeling within the Actuarial Strategic Modeling (ASM) department. This leadership role offers a unique opportunity to drive innovation in predictive modeling, machine learning, and actuarial analytics in either personal auto, or both personal auto and homeowners depending on background. You will manage a high-performing team of data scientists and actuaries, collaborating with cross-functional partners in actuarial, data engineering, and other modeling organizations to deliver modeling solutions that directly impact business strategy. The ASM group is committed to advancing model workflows through scalable systems, and continuous model delivery—and is searching for a leader to guide and shape this innovative direction.

Requirements

8+ years of relevant analytical experience recommended.
Master’s or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or a relevant professional designation (e.g. FCAS, FSA, CSPA, ACAS, ASA)
Expertise in statistical modeling, inference, and building machine learning algorithms in Python and/or R.
Prior Management Experience
Expertise in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation.
Experience in SQL and familiarity with cloud-native environments (e.g., Snowflake, Sagemaker).
Able to communicate effectively with both technical and non-technical audiences.
Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution

Responsibilities

Lead Personal Insurance Actuarial Modeling: Serve as the model owner for personal insurance predictive models within actuarial, ensuring alignment with ratemaking and business priorities. Partner on strategic vision while managing team capacity and driving timely model deliverables.
Model Development & Deployment: Lead design, maintenance, and deployment of predictive models for frequency, severity, and loss cost estimates, ensuring production readiness and effective integration into actuarial workflows.
Cross-Functional Collaboration: Partner with Actuarial, Data Engineering, and other modeling organization teams to connect modeling initiatives with ratemaking strategies and organizational goals, promoting shared problem-solving.
Innovation: Drive modernization through advanced modeling techniques, machine learning, and AI to enhance efficiency and decision-making. Lead experimentation with new data sources, features, and methodologies to uncover insights and advance strategic objectives.
Operational Excellence: Ensure robust documentation, validation, and governance, along with scalable processes to monitor model performance and maintain reliability.
Talent Development: Mentor and develop team members, fostering a culture of curiosity, ownership, and continuous learning. Support hiring and onboarding, including intern and actuarial student rotations.
Strategic Influence: Participate in enterprise initiatives to ensure personal insurance predictive models are efficiently integrated into core data and system platforms.