AI/Data Science Engineer II

MiniMed is a full-stack insulin delivery company dedicated to supporting people living with diabetes. The AI/Data Science Engineer II role focuses on delivering big-data analytics solutions that drive decision support for the business, bridging advanced data engineering with applied data science.

Responsibilities:

• Partner with engineers and scientists to design and deliver analytical models, dashboards, and data pipelines that translate complex product datasets into actionable insights supporting product design decisions
• Design, build, and optimize SQL-based queries and data models across large-scale relational and cloud data warehouse environments, including ETL/ELT pipeline development and maintenance
• Apply Python-based data analysis and visualization tools (pandas, matplotlib, seaborn, plotly, etc.) to develop scalable, reusable analytical solutions
• Explore and integrate AI-assisted development tools (e.g., Windsurf, GitHub Copilot) to improve development velocity and code quality, and prototype machine learning models to support predictive analytics use cases
• Communicate findings clearly to both technical and non-technical stakeholders through polished visualizations, reports, and presentations
• Contribute to data infrastructure strategy, including schema design, data governance, and warehouse performance

Requirements:

• Requires a Bachelor's Degree and minimum of 2 years of relevant experience, or advanced degree with 0 years of experience
• Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, or related field
• 3-5 years (1-3 years if master's degree) of hands-on experience deriving insights and driving decisions from large, complex datasets
• Advanced proficiency - complex joins, window functions, CTEs, query optimization
• Hands-on experience with platforms such as Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse
• Proficient in pandas, NumPy, and data visualization libraries (matplotlib, seaborn, plotly)
• Solid working knowledge of foundational statistical concepts - hypothesis testing, distributions, regression, and sampling methods - applied to real-world product and quality datasets
• Ability to translate technical findings into clear, actionable insights for cross-functional audiences
• Familiarity with ETL/ELT workflows and pipeline tooling
• Experience with cloud platforms (AWS, Azure, GCP) in a data context
• Experience or genuine interest in medical technology, clinical studies, or healthcare data - strongly preferred
• A passion for turning complex data into compelling narratives that drive action - strongly preferred
• Familiarity with advanced statistical techniques such as multivariate analysis, survival analysis, or statistical process control (SPC)
• Experience with AI-assisted coding environments such as Windsurf, GitHub Copilot, or similar
• Familiarity with scikit-learn or similar ML frameworks for classification, regression, or anomaly detection
• Experience with Power BI, Tableau, or similar dashboard/reporting platforms