Boston Scientific

Data Science Co-op - Spring or Summer 2027

Boston Scientific

Maple Grove US-MN · Posted Sep 17

$43k–$74k/yr Data Hybrid
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Location: Maple Grove US-MN, United States | N/A Department: Interns/Graduates

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 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

Preferred Qualifications:

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.

Ability to communicate technical findings effectively to multidisciplinary teams.

Detail-oriented with strong problem-solving and organizational skills.

Interest in applying data science to healthcare and medical device innovation.

Previous internship or co-op experience

Desire to work in a medical device company where real products get manufactured

Requisition ID: 634924

Minimum Salary: $ 43368

Maximum Salary: $ 73736

The anticipated compensation listed above and the value of core and optional employee benefits offered by Boston Scientific (BSC) – see www.bscbenefitsconnect.com—will vary based on actual location of the position and other pertinent factors considered in determining actual compensation for the role. Compensation will be commensurate with demonstrable level of experience and training, pertinent education including licensure and certifications, among other relevant business or organizational needs. At BSC, it is not typical for an individual to be hired near the bottom or top of the anticipated salary range listed above.

Compensation for non-exempt (hourly), non-sales roles may also include variable compensation from time to time (e.g., any overtime and shift differential) and annual bonus target (subject to plan eligibility and other requirements).

Compensation for exempt, non-sales roles may also include variable compensation, i.e., annual bonus target and long-term incentives (subject to plan eligibility and other requirements).

For MA positions: It is unlawful to require or administer a lie detector test for employment. Violators are subject to criminal penalties and civil liability.

Boston Scientific transforms lives through innovative medical technologies that improve the health of patients around the world. As a global medical technology leader for more than 45 years, we advance science for life by providing a broad range of high-performance solutions that address unmet patient nee

What they are looking for

Python Pandas Numpy Scipy Scikit-learn

Details

Work type
Hybrid
Compensation
Paid
Visa sponsorship
Not offered
Remote eligible
No

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