Description
The Innovation & Technology - Data Science Internship is a 10.5-week full-time opportunity that begins on May 24th, 2027, and concludes on August 4th, 2027.
This is a hybrid position based in New York, NY, with three in-office days per week, generally Tuesday, Wednesday, and Thursday. The remaining two days may be worked remotely from home or another location of your choice.
As a CVS Health Corporate intern, you will participate in projects that contribute to the success of the business, community service activities, professional development workshops, mentorship and networking opportunities, and interaction with senior leaders.
Your Innovation & Technology internship experience will also include:
- Leadership Insight Series, featuring leader spotlights and interactive Q&A sessions
- Intern Innovation Challenge, providing opportunities to collaborate with fellow interns across Innovation & Technology
- Additional learning experiences focused on topics such as impactful presentations and storytelling, emerging technology, and AI tools
The hourly rate is $51.60, based on a 40-hour workweek. The internship includes two days of paid leave and no work on the July 4 company holiday.
As a Data Science intern, you'll apply statistical methods and machine learning to real problems across the business. Working alongside experienced data scientists, engineers, and business partners, you'll analyze large datasets, build and evaluate predictive models, design experiments, and translate your findings into actionable recommendations.
You'll have opportunities to:
- 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
Required Qualifications:
- 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
Preferred Qualifications:
- 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 both technical and non-technical audiences