AI/Data Science Engineer II

We anticipate the application window for this opening will close on 7 Jul 2026. About the Role This AI/Data Science Engineer II role focuses on delivering big-data analytics solutions that drive decision support for the business. The role bridges advanced data engineering with applied data science to enable smarter product design decisions and robust quality reporting and investigation support. 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. Required Knowledge and Experience Bachelor’s Degree and minimum of 2 years of relevant experience, or advanced degree with 0 years of experience. Advanced proficiency in SQL – complex joins, window functions, CTEs, query optimization. Hands‑on experience with Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse. Proficiency in Python (pandas, NumPy, matplotlib, seaborn, plotly). Solid working knowledge of foundational statistical concepts – hypothesis testing, distributions, regression, sampling methods. Familiarity with ETL/ELT workflows and pipeline tooling. Experience with cloud platforms (AWS, Azure, GCP) in a data context. Ability to translate technical findings into clear, actionable insights for cross-functional audiences. Preferred Qualifications Education: Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, or related field. Experience: 3–5 years (1–3 years if master’s degree) of hands‑on experience deriving insights and driving decisions from large, complex datasets. Experience with AI-assisted coding environments such as Windsurf or GitHub Copilot. Experience with scikit‑learn or similar ML frameworks for classification, regression, or anomaly detection. Experience with Power BI, Tableau, or similar dashboard/reporting platforms. Experience or genuine interest in medical technology, clinical studies, or healthcare data. Strong data storytelling skills. Knowledge of advanced statistical techniques such as multivariate analysis, survival analysis, or statistical process control (SPC). Physical Job Requirements The above statements describe the general nature and level of work performed by employees assigned to this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of this job. For office roles, the employee must be independently mobile and interact with a computer and peers. Please consult your manager or local HR for specific work conditions. Equal Employment Opportunity Statement MiniMed is an equal opportunity employer. We provide reasonable accommodations for qualified individuals with disabilities. We comply with all applicable federal, state, and local laws. MiniMed participates in the federal E‑Verify program to confirm employment eligibility. #J-18808-Ljbffr USA-Medtronic MiniMed, Inc 1017