Data Science Intern

The Hartford

. Develop machine learning and artificial intelligence solutions across strategic initiatives .

Posted 9/17/2026full-timeHartford • Connecticut • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing machine learning and artificial intelligence solutions, with a strong foundation in statistical modeling and data analysis. Proficient in communicating complex methodologies and insights to diverse audiences while maintaining organized documentation and project management.

Highest-signal resume keywords

Machine Learning AlgorithmsStatistical ModelingPython ProgrammingCloud-Native EnvironmentsStrong Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningData AnalysisPythonSQLUnixGitPrompt EngineeringRAGLLM Evaluation

Soft Skills

Communication SkillsOrganizational Skills

Tools & Technologies

AWS SagemakerGCP Agent Platform

Industry Keywords

Data ScienceApplied MathematicsQuantitative EconomicsActuarial ScienceBusiness Processes

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPythonSQLUnix

About the role

Key responsibilities & impact

Develop machine learning and artificial intelligence solutions across strategic initiatives
Assist in creating statistical models, machine learning models, and AI workflows to solve business problems
Review work with business partners and team members to calibrate deliverables against expectations
Identify and assess the value of new data sources and analytical techniques
Participate in creating and deploying long-term tools to evolve the business
Contribute to implementing strategies to achieve targeted business objectives
Develop knowledge of The Hartford’s structures, business processes, and data sources
Remain current on research techniques and state-of-the-art tools
Provide economic, qualitative, and statistical support for business decisions
Prepare and deliver presentations translating data-driven insights, model results, and recommendations
Document work clearly for effective knowledge sharing

Requirements

What you’ll need

Must be authorized to work in the United States without sponsorship now or in the future
Must be working towards a Master’s or Ph.D. in Data Science, Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Computer Science, or a similar analytical field
Experience in statistical modeling, inference, and building machine learning algorithms using Python
Strong communication skills for explaining methodologies, visualizations, and recommendations to non-technical audiences and vice versa
Able to maintain organized project notes, version history, and technical documentation for team reference
Exposure to building modeling solutions in cloud-native environments, such as AWS Sagemaker or GCP Agent Platform, a plus
Understanding of prompt engineering, retrieval-augmented generation (RAG), agent workflow, and LLM evaluation, a plus
Exposure to SQL and navigating databases to extract relevant attributes, a plus
Exposure to Unix and Git, a plus

Benefits

Comp & perks

Hybrid work location model with remote flexibility on Monday and Friday
On-the-job training in insurance, cloud development environments, and modeling/machine learning techniques
Opportunities to present to senior Data Science leaders
Networking across all levels of the Data Science & Analytics community
Social events
Discussions with leaders via one-on-ones and panels
Potential short-term or annual bonuses
Potential long-term incentives
On-the-spot recognition