Associate Data Scientist, Personal Lines

The Hartford

. Develop and evaluate predictive modeling solutions supporting the personal auto class plan, unconstrained loss models, and customer demand models.

Posted 11/10/2026full-timeUnited StatesJuniorMid-Level💰 $81,040 - $121,560 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in predictive modeling, particularly in the insurance domain, with a strong foundation in statistical techniques and programming. Proficient in utilizing cloud-based MLOps tools and maintaining analytic reproducibility while collaborating effectively within an Agile framework.

Highest-signal resume keywords

Predictive ModelingGeneralized Linear ModelsPython ProgrammingGitHub Version ControlCloud-Native Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Predictive Modeling SolutionsLoss Cost ModelingGeneralized Linear ModelsRidge RegressionLasso RegressionGAMsData AnalysisFeature EngineeringAnalytic PackagesMachine Learning Techniques

Soft Skills

CollaborationProblem-SolvingResearch SkillsCommunicationWorkflow Improvement

Tools & Technologies

MLOps ToolsCloud-Based EnvironmentsSageMakerGitAgile Framework

Industry Keywords

Insurance IndustryPersonal Insurance ProductsData ScienceStatisticsActuarial Science

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

Develop and evaluate predictive modeling solutions supporting the personal auto class plan, unconstrained loss models, and customer demand models.
Evaluate new data sources and modeling approaches to improve product performance.
Engineer features to uncover additional signal for models.
Support model implementations with state Departments of Insurance, serve as a subject matter expert, and respond to DOI queries.
Maintain repositories and scripts and suggest workflow improvements.
Assist in modernizing model deployments using cloud-based MLOps tools.
Collaborate with team members to plan and deliver projects in an Agile framework.
Develop and maintain analytic packages for data collection, analysis, and modeling.
Stay current on machine learning techniques, apply them, and share them with the team and broader data science community.
Ensure analytic reproducibility, conduct code reviews, and maintain Git hygiene.
Share results with partners and make recommendations based on outcomes.

Requirements

What you’ll need

Master's degree in Statistics, Data Science, Mathematics, Actuarial Science, Economics, Engineering, Physics, or similar analytical field.
Experience in the insurance industry, particularly in loss cost modeling or personal insurance products, is a plus but not required.
Relevant modeling experience from other industries.
Comfort with generalized linear models and related techniques, including ridge and lasso regression and GAMs, and the math behind them.
Hands-on experience with Python and a track record of delivering clean, literate code in a reproducible environment.
Experience using GitHub for version control, documentation, code collaboration, and technical project management.
Ability to independently research solutions, identify when stuck, and seek help when needed.
Strong interest in identifying and eliminating workflow inefficiencies.
Experience tracking down root causes of problems and identifying tradeoffs.
Demonstrated experience listening to collaborators and brainstorming outcomes that address business problems.
Experience building modeling solutions in cloud-native environments, such as SageMaker, is a plus.
Commitment to democratizing knowledge, evangelizing good practices, and supporting peers.
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.

Benefits

Comp & perks

Short-term or annual bonuses
Long-term incentives
On-the-spot recognition
Hybrid work schedule