Associate Data Scientist, Personal Lines

Company: The Hartford

Location: Charlotte, NC

Salary: $81k - $121.6k per year

Type: Full-time

Posted: 2026-11-10

About this role

Assoc Data Scientist - GD08BE

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.   

         

The Hartford seeks an energetic and passionate Associate Data Scientist to build high-performing, empathetic analytics teams and deliver smarter product pricing decisions. This role will focus on the Auto line within the Personal Insurance Loss and Demand Modeling team. We support our product and pricing partners through the delivery of rigorously developed and tested solutions including models and implementation support.

In this role, you will contribute across the full model lifecycle, from data exploration and feature engineering through model development, validation, implementation, and monitoring. Generalized linear models are a core component of our work, alongside machine learning techniques such as gradient boosted trees and modern MLOps practices. You will also help improve the tools, workflows, and standards that enable the team to support a broad and evolving portfolio of models.

Responsibilities:

  • Develop and evaluate predictive modeling solutions that support the personal auto class plan, unconstrained loss models, and customer demand models.
  • Evaluate new data sources and modeling approaches to boost product performance. Engineer features to uncover additional signal for our models.
  • Support model implementations with state Departments of Insurance (DOI), serving as a subject matter expert on the models you build and responding to DOI queries.
  • Maintain a portfolio of repositories and scripts and suggest improvements to workflows. Assist in the modernization of model deployments using our cloud-based MLOps tools.
  • Collaborate with team members to plan and deliver projects in an Agile framework.
  • Develop and ...

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