Data Science Co-op- Summer 2026

Additional Location(s):  N/A

 

Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance

 

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.       

 

About the role:

 

 

We will consider qualified applicants of all ages who are starting (or restarting) their careers

 

At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model, requiring employees to be in our local office at least four days per week.

 

Relocation and housing assistance may be available to those who meet the eligibility criteria.

 

Boston Scientific will not offer sponsorship or take over sponsorship of an employment VISA for this position at this time

 

 

As a Data Science Co-op participant, you will play a key role in supporting cross-functional teams by leveraging data-driven insights to improve product quality, process efficiency, and business decision-making. You will gain hands-on experience working with large datasets, developing predictive models, and building data pipelines that support advanced analytics and process development initiatives. This role offers a unique opportunity to apply data science techniques in a real-world medical device manufacturing environment, contributing to innovation and continuous improvement at Boston Scientific.

 

Your responsibilities will include:  

• 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.

 

Required Qualifications: 

• Must graduate between December 2026 – Spring 2028

• Currently pursuing a bachelor’s or graduate level degree majoring in Data Science, Business Analytics, Computer Science or Mathematics

• Must be able to commit to the 8-month co-op program period: May 18th or May 26th – December 19th
• 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

 

Preferred Qualifications:

• 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.
• Ability to communicate technic