Director of Data Science

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.

Qualifications:

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

This role can have a Hybrid work arrangement in one of our hub offices. Candidates who live near one of our office locations will have the expectation of working in an office three days a week (Tuesday through Thursday). Candidates who do not live near an office may be considered for a remote work arrangement with occasional travel.

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:
$153,200 - $229,800
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

Client-provided location(s): Charlotte, NC

Job ID: Hartford_Fire_Insurance_Company_FGB-4548

Employment Type: FULL_TIME

Posted: 2026-05-21T18:48:40