Director of Data Science

The Hartford

Director of Data Science at The Hartford overseeing Personal Insurance modeling and driving predictive analytics innovation. Leading a team of data scientists for impactful business strategies.

Posted 5/20/2026full-timeHartford • Connecticut, Illinois, North Carolina • 🇺🇸 United StatesLead💰 $153,200 - $229,800 per yearWebsite

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Benefits

Comp & perks

short-term or annual bonuses
long-term incentives
on-the-spot recognition

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

statistical modelingmachine learningPythonRSQLmodeling lifecycledata analysispredictive modelinginferencedata integration

Soft Skills

leadershipcommunicationmentoringcollaborationproblem-solvingstrategic thinkingcuriosityownershipcontinuous learninginfluence

Certifications

FCASFSACSPAACASASA