The Hartford is offering an 11-week Data Science Summer Internship Program beginning in May 2027 designed to prepare you for a challenging and rewarding Data Science career. 

As a Data Scientist Intern, you will develop machine learning and artificial intelligence solutions across a range of strategic initiatives. Additionally, you will have opportunities to present to senior Data Science leaders, network across all levels of our Data Science & Analytics community, attend social events, and discussions with leaders via one-on-ones and panels.  To accelerate your project work, we also provide on-the-job training in insurance, cloud development environments, and modeling/machine learning techniques as needed. 

The Hartford is proud to offer a hybrid work location model that is designed to support flexibility and collaboration, where you will work in an office (CT- Hartford, NC- Charlotte or IL- Chicago) on Tuesday, Wednesday, and Thursday with remote flexibility on Monday and Friday. 

Responsibilities: 

• Assist in creating statistical models, machine learning models, and AI workflows to solve business problems 

• Participate in reviewing work with business partners and team members on an ongoing basis to calibrate deliverables against expectations 

• Assist in identifying and assessing the value of new data sources and analytical techniques to ensure ongoing competitive advantage 

• Participate in the creation and deployment of long-term tools to continually evolve the business 

• Contribute to the successful implementation of strategies to achieve targeted business objectives 

• Develop knowledge of The Hartford's formal and informal structures, business processes, and data sources in your area of expertise 

• Remain current on research techniques and become familiar with state-of-the-art tools applicable to your function 

• Provide economic, qualitative, and statistical support to ensure accuracy of characteristics and metrics being applied to business decisions  

• Prepare and deliver presentations that translate data-driven insights, model results, and recommendations to varying business partners 

• Document work clearly to ensure effective knowledge sharing within the team 

Requirements:  

• 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