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# Data Scientist

- **Company:** Boston, Inc.
- **Location:** Arden Hills, MN, United States
- **Experience:** Starter
- **Salary:** $59,900 - $113,800
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Data Analysis, ARM Architecture, Information Extraction, Python (Programming Language), Machine Learning, Search Technologies, Software Engineering, SQL Databases, Enterprise Data Management, Feature Engineering, Large Language Models, Snowflake, Feature Selection, Model Context Protocol, Meditech
- **Published:** October 12, 2026
- **Apply:** https://diversityjobs.com/career/18629362/Data-Scientist-Minnesota-Arden-Hills

## About the Role

* Must graduate with your bachelor's degree majoring in Computer Sciencein December 2026
 * Must be eligible to work in the U.S. without company sponsorship, now or in the future, for employment-based work authorization
 * Must have prior software engineering internship experience from Boston Scientific
 * Must have minimum of 0-1 year of work experience in MedTech
 * Must have minimum of 1+ year of work experience in software development

## Description

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 three-four days per week., We are seeking a passionate and motivated Data Scientistto support our Data & AI Commercial Data Products Team. This role will apply statistical analysis, machine learning, advanced analytics, and artificial intelligence to solve complex business problems, generate actionable insights, and develop data-driven solutions that improve Commercial decision-making and operational effectiveness.
The Data Scientist will work closely with business partners, data engineers, AI/ML teams, and other cross-functional stakeholders to identify high-value opportunities and translate business challenges into analytical solutions. The role will be responsible for exploring and analyzing complex datasets, developing predictive and statistical models, evaluating model performance, and communicating findings and recommendations to technical and non-technical audiences.
In addition to traditional data science capabilities, this role will contribute to the development ofgenerative AI and intelligent agent solutionsusing technologies such asSnowflake Cortex, large language models (LLMs), and Model Context Protocol (MCP). The Data Scientist will help evaluate where these emerging technologies can complement traditional analytics and machine learning approaches to create scalable, secure, and responsible solutions., * Partner with Commercial business teams and cross-functional stakeholders to identify and prioritize opportunities wheredata science, advanced analytics, machine learning, and AIcan address business challenges and improve decision-making.

 * Translate business problems into well-defined analytical questions, hypotheses, data requirements, and measurable success criteria.
 * Design, develop, and evaluate predictive and machine learning models for use cases such as forecasting, segmentation, classification, propensity modeling, optimization, and other Commercial applications.
 * Perform feature engineering, feature selection, model training, validation, tuning, and performance evaluation to develop accurate, interpretable, and reliable models.
 * Develop reusable analytical workflows using Python, SQL, and Snowflake to support data exploration, statistical analysis, machine learning, and AI applications.
 * Collaborate with data engineers to identify data requirements, prepare analytical datasets, and ensure data used for modeling and analysis is accurate, reliable, appropriately governed, and fit for purpose.
 * Develop and prototype generative AI solutionsusing Snowflake Cortex and large language models, including capabilities such as summarization, classification, information extraction, embeddings, semantic search, and natural language interaction with enterprise data.
 * Implement and evaluate Model Context Protocol (MCP)and related integration approaches to securely provide enterprise data and contextual information to LLM and agent-based solutions.