Data Science Co-op - Spring or Summer 2027

Boston Scientific is a global medical technology company that develops innovative devices and therapies to improve patient health. The Data Science Co-op will support cross-functional teams by analyzing experimental and production data, developing predictive models and dashboards, and applying machine learning and generative AI to improve product quality, process efficiency, and business decision-making.

What you'll do:

• Collect, clean, and preprocess experimental and production process data for analysis
• Collaborate with cross-functional teams to identify high-value use cases where generative AI can accelerate process development and innovation
• Explore applications of large language models (LLMs) and develop prompt engineering strategies for such areas as automating documentation and report drafting
• Apply statistical methods and machine learning techniques to identify trends, correlations, and areas for process improvement
• Develop predictive models and dashboards to support decision-making in process development
• Collaborate with process engineers, scientists, quality teams and others to translate business and technical needs into analytical solutions
• Document data workflows, models, and analysis results in a clear and reproducible manner
• Create visualizations and reports to communicate findings to both technical and non-technical stakeholders
• Contribute to automation of data analysis pipelines and integration of tools/software

What they're looking for:

• Must graduate between December 2027 – Spring 2028
• Currently pursuing a bachelor's or graduate level degree majoring in Data Science, Industrial Engineering, Computer Science or Applied Mathematics/Statistics
• Must be able to commit to the 8-month co-op program period: + January 11th - August 6th or 13th, 2027 + May 17th or May 24th – December 17th, 2027
• Must be eligible to work in the U.S. without company sponsorship, now or in the future, for employment-based work authorization
• Must have reliable transportation to and from the Maple Grove, MN Boston Scientific Corporate location
• Must be proficient in Python
• Minimum of 3 months to 1 year of experience in applying machine learning techniques through coursework, internships, research, or project work
• Pursuing a graduate level degree
• Experience with data manipulation libraries (e.g., pandas, NumPy, SciPy) and visualization tools (e.g., matplotlib, seaborn, Plotly)
• Familiarity with machine learning frameworks (e.g., scikit-learn, PyTorch, TensorFlow, or similar)
• Knowledge of experimental design, statistical analysis, and hypothesis testing
• Experience working with structured data (SQL, relational databases) and unstructured datasets

Benefits:

• Hybrid work model, requiring employees to be in the local office at least four days per week.
• Relocation and housing assistance may be available to those who meet the eligibility criteria.
• Access to the latest tools, information and training to advance skills and career.
• Support in progressing, whatever your ambitions.
• Variable compensation from time to time, including overtime and shift differential, for non-exempt (hourly), non-sales roles, subject to plan eligibility and other requirements.
• Annual bonus target for non-exempt (hourly), non-sales roles, subject to plan eligibility and other requirements.
• Annual bonus target and long-term incentives for exempt, non-sales roles, subject to plan eligibility and other requirements.