Sports Data Science Internship Jobs in Springfield, MA

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.   

Tech & Data Program Summer 2027 – Data Engineer Intern

Program Overview 

At The Hartford, we foster an inclusive and collaborative environment where every voice is valued and every idea can make an impact. Our culture is built on integrity, innovation, and a customer-first mindset. We believe in empowering employees to grow through continuous learning, mentorship, meaningful work, and opportunities to contribute to solutions that support our customers and business.

As a Data Engineer Intern, you will help build and support the data pipelines, platforms, and processes that enable analytics, reporting, automation, and AI-driven insights across the organization. This role is ideal for students who are interested in building the systems behind the data — transforming raw information into reliable, usable data assets that help teams make better decisions.

Bring your curiosity, technical mindset, and willingness to learn. Your voice and perspective matter here.

About the Experience

The Hartford’s Technology, Data, AI, and Operations organization offers an immersive summer internship program designed to help students explore career paths in technology, data engineering, cybersecurity, AI, analytics, data science, and technology operations within the insurance industry.

As part of The Hartford’s growing investment in AI and advanced analytics, interns will explore how emerging technologies — including generative AI, machine learning, and automation — are transforming business operations, decision-making, and customer experience.

In this role, you will gain hands-on experience supporting data solutions that help power business insights, analytics products, and future AI capabilities.

This role is a hybrid position in Hartford, CT. or in the future. Candidate 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.

What You'll Gain 

• Hands-on experience designing, building, and supporting data pipelines and data workflows
• Exposure to modern data engineering practices, including ETL/ELT, data transformation, data quality, and cloud-based data platforms
• Opportunities to work with tools and technologies such as Python, SQL, PL/SQL, Snowflake, GitHub, and cloud platforms
• Exposure to how data engineering enables analytics, reporting, automation, machine learning, and AI use cases
• Mentorship, coaching, feedback, and self-directed learning opportunities
• Networking, volunteerism, and employee engagement experiences with peers and leaders across the organization
• A stronger understanding of how data supports decision-making within the insurance industry

Ways You'll Learn, Grow, and Contribute

Depending on your role and project assignments, your experience may include:

• Build and support data pipelines that ingest, transform, and prepare data for business and analytical use
• Work with structured and unstructured data to enable analytics, reporting, and AI-driven solutions
• Apply data engineering tools and techniques (e.g., Python, SQL, ETL processes, cloud technologies) to develop reliable data assets
• Ensure data quality, consistency, and performance through profiling, validation, and monitoring activities
• Collaborate with cross-functional teams to deliver scalable data solutions that address business needs
• Leverage AI tools (e.g., Copilot) to enhance productivity and support the development of data solutions that power advanced analytics and machine learning

Required Qualifications

• Undergraduate or graduate student expecting to graduate in May 2028 with a Bachelor's or Master's degree and a GPA of 3.0 or higher.
• Pursuing a degree in Computer Science, Engineering, IT, Management Information Systems, Data Analytics, Applied Mathematics, or another STEM-related field

• Strong analytical, problem-solving, and critical thinking skills
• Strong communication, collaboration, and interpersonal skills
• Curiosity and willingness to explore new technologies and challenge assumptions
• Demonstrated ability to analyze complex problems using structured thinking and logical reasoning
• Commitment to ethical judgment, responsible data use, and understanding how technology decisions affect stakeholders and the business

Experience and exposure to some or all of the following: 

• Programming & Querying: Python, SQL, PL/SQL

• Data Engineering: ETL/ELT, data pipelines, data transformation, data profiling, data quality, data modeling
• Data Platforms & Tools: Snowflake, GitHub, relational databases, data warehouse concepts
• Cloud Technologies: AWS, Azure, or Google Cloud
• Analytics & BI: Tableau, dashboards, reporting, data mining, or business intelligence tools
• AI & Emerging Technology: Familiarity with AI/ML concepts, generative AI tools, LLMs, NLP, or interest in building data foundations that support AI-driven solutions
• Agile Ways of Working: Exposure to Agile teams, sprint delivery, or collaborative product-based work.

Our internship program is designed as a pipeline for future full-time opportunities. High-performing interns may be considered for full-time roles within The Hartford’s Technology & Data organization.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

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