Junior Data Scientist

Additional Location(s): US-MA-Marlborough

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:

Boston Scientific is seeking a Junior Data Scientist to join our growing Enterprise AI Team. This hybrid role offers the opportunity to develop, evaluate, and support AI/ML and data-driven solutions across multiple business functions. It’s a hands-on position ideal for someone with a strong foundation in data science, a growth mindset, and early career experience in real-world data projects.

 

As a Junior Data Scientist, you’ll collaborate with Senior Data Scientists and cross-functional teams to build impactful AI/ML models, conduct analysis, and contribute to our expanding portfolio of use cases. Your work will help shape how Boston Scientific leverages advanced analytics to drive innovation and value for patients, clinicians, and the business.

 

 

Work model, sponsorship, relocation:

At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our local office in Marlborough, MA at least three days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time. Relocation assistance is not available for this position at this time.

 

 

Your responsibilities will include:

● Assist in designing, training, evaluating, and validating statistical and machine learning models.

● Support data cleaning, feature engineering, exploratory analysis, and experiment setup.

● Contribute to the development of reproducible code, notebooks, and ML pipelines.

● Work with structured and unstructured datasets from internal and external sources.

● Partner with engineering, architecture, and data platform teams to understand data quality and availability.

● Conduct literature reviews, benchmark research, and support prototyping of algorithms and modeling techniques.

● Translate technical findings into clear summaries, visualizations, and recommendations for business and technical audiences.

● Collaborate with cross-functional partners to understand requirements and business problems.

● Participate in agile ceremonies, project planning sessions, and model review discussions.

● Assist in preparing models for deployment by organizing data inputs, testing workflows, and documenting model logic.

● Follow best practices related to responsible AI, data privacy, and model monitoring.

● Contribute to internal knowledge sharing, workshops, and team learning opportunities.

● Stay current with emerging techniques in machine learning, GenAI, and applied analytics.

 

 

Qualifications:

 

Required qualifications:

● Bachelor’s degree in Computer Science, Data Science, Statistics, Computational Biology, Engineering, or a related field.

● Minimum of 2 years' experience in data science, applied machine learning, analytics, or computational research (industry, academic, or internship).

● Proficiency in Python and common data/ML libraries (e.g., NumPy, Pandas, scikit-learn).

● Ability to analyze data, run experiments, and communicate findings clearly.

● Strong problem-solving skills and curiosity for applied AI.

 

 

Preferred qualifications:

● Master’s degree in Computer Science, Data Science, Statistics, Computational Biology, Engineering, or related field.

● Experience with scientific computing, healthcare data, or biological/clinical datasets.

● Exposure to cloud computing environments such as AWS, Azure, or Snowflake.

● Familiarity with ML Ops tools, workflow orchestration, or API development.

● Experience teaching, mentoring, or supporting technical coursework (a plus, not required).

● Basic understand