Innovation & Technology Internship - Data Science - Summer 2027 (Graduate)

CVS Health•New York, NY

3d•Hybrid

About The Position

The Innovation & Technology Data Science Internship is a 10.5-week, full-time hybrid internship based in New York, NY, running from May 24, 2027, through August 4, 2027. Interns work in the office three days per week, generally Tuesday through Thursday, and may work remotely the other two days. Relocation assistance is available for candidates who need to relocate more than 50 miles. As a Data Science intern with CVS Health’s Analytics & Behavior Change team, you will work alongside data scientists, engineers, and business partners to apply statistical methods and machine learning to business and health care challenges. You will analyze large datasets, build and evaluate predictive models, design experiments, and communicate actionable recommendations. The team uses analytics, machine learning, behavioral science, and AI to support areas such as patient outcomes, health equity, digital experiences, and enterprise value. The internship includes business-contributing projects, community service activities, professional development workshops, mentorship and networking opportunities, and interaction with senior leaders. Innovation & Technology programming also includes a Leadership Insight Series, an Intern Innovation Challenge, and learning experiences on presentations, storytelling, emerging technology, and AI tools. The hourly pay rate is $51.60 for a 40-hour workweek. The internship includes two days of paid leave and no work on the July 4 company holiday. Relocation assistance is provided when applicable. Work visa sponsorship is not available, including CPT, OPT, and F-1 Visa programs. The role is intended for a student currently pursuing a master’s degree and expecting to graduate between December 2027 and June 2028. Preferred areas of study include Statistics, Biostatistics, Mathematics, Data Science, Health Data Science, Operations Research, or a related quantitative field.

Requirements

Currently pursuing a master’s degree, with an expected graduation date between December 2027 and June 2028.
Knowledge of data science techniques, including statistical analysis, predictive modeling, and machine learning.
Experience using Python or R for data analysis and modeling.
Experience using SQL to query and analyze data.
Exposure to experimental design and quantitative methods, such as A/B testing and causal analysis.

Nice To Haves

Preferred fields of study include Statistics, Biostatistics, Mathematics, Data Science, Health Data Science, Operations Research, or a related quantitative field.
Familiarity with machine learning libraries and frameworks, such as scikit-learn, for building and evaluating models.
Experience analyzing large, complex datasets to identify patterns and insights.
Strong problem-solving and critical-thinking skills applied to ambiguous or open-ended analytical questions.
Experience communicating analytical findings through data visualizations, written summaries, and presentations to support decision-making.
Ability to clearly explain technical concepts and their implications to technical and non-technical audiences.

Responsibilities

Analyze structured and unstructured data to uncover patterns and insights.
Build, test, and evaluate predictive and machine learning models.
Design and analyze experiments to inform business decisions.
Create visualizations and communicate findings to technical and business audiences.
Contribute to solutions that improve health care quality, affordability, and outcomes.
Translate analytical findings into actionable recommendations.
Participate in business projects, community service, professional development, mentorship, networking, and leadership programming.