AI/Data Science Engineer II

MiniMed•Minneapolis, MN

2d•$87,000 - $149,000

About The Position

The AI/Data Science Engineer II delivers big-data analytics and AI solutions to support business decision-making. The role bridges applied data science and advanced AI to inform product design decisions and support quality reporting and investigations. The engineer partners with engineers and scientists to create analytical models, dashboards, and data pipelines, and contributes to data infrastructure strategy, including schema design, data governance, and warehouse performance. The role also explores AI-assisted development tools and prototypes machine-learning models for predictive analytics. MiniMed is a full-stack insulin delivery company focused on supporting people living with diabetes. The position requires a bachelor’s degree and at least two years of relevant experience, or an advanced degree with no experience. The application window is anticipated to close on October 25, 2026.

Requirements

Bachelor’s degree and a minimum of two years of relevant experience, or an advanced degree with zero years of experience.
Proficiency in Python, including pandas, NumPy, and data visualization libraries such as Matplotlib, Seaborn, and Plotly.
Advanced SQL proficiency, including complex joins, window functions, CTEs, and query optimization.
Solid working knowledge of foundational statistical concepts, including hypothesis testing, distributions, regression, and sampling methods.
Ability to translate technical findings into clear, actionable insights for cross-functional audiences.
The physical requirements for office roles include being independently mobile, interacting with a computer, and communicating with peers and co-workers.

Nice To Haves

Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, or a related field.
Three to five years of hands-on experience deriving insights and driving decisions from large, complex datasets; one to three years with a master’s degree.
Experience with data warehousing platforms such as Databricks, Snowflake, AWS Redshift, BigQuery, or Azure Synapse.
Familiarity with ETL/ELT workflows and pipeline tooling.
Experience with AWS, Azure, or GCP in a data context.
Experience or genuine interest in medical technology, clinical studies, or healthcare data.
Interest in turning complex data into compelling narratives that drive action.
Familiarity with multivariate analysis, survival analysis, or statistical process control (SPC).
Experience with Power BI, Tableau, or similar dashboard and reporting platforms.
Familiarity with scikit-learn or similar machine-learning frameworks for classification, regression, or anomaly detection.
Experience with AI-assisted coding environments such as Windsurf/Devin, GitHub Copilot, or similar tools.
Experience building production-level GenAI solutions to solve real-world problems.

Responsibilities

Partner with engineers and scientists to design and deliver analytical models, dashboards, and data pipelines that turn complex product datasets into actionable insights for product design decisions.
Use Python-based data analysis and visualization tools, including Pandas, Matplotlib, Seaborn, and Plotly, to develop scalable and reusable analytical solutions.
Design, build, and optimize SQL queries and data models across large-scale relational databases and cloud data warehouses, including developing and maintaining ETL/ELT pipelines.
Explore and integrate AI-assisted development tools to improve development velocity and code quality, and prototype machine-learning models for predictive analytics use cases.
Communicate findings to technical and non-technical stakeholders through visualizations, reports, and presentations.
Contribute to data infrastructure strategy, including schema design, data governance, and warehouse performance.

Benefits

Competitive salary and flexible benefits package.
Health, dental, and vision insurance.
Health Savings Account and Healthcare Flexible Spending Account.
Life insurance and long-term disability leave.
Dependent daycare spending account.
Incentive plans, including eligibility for the Short Term Incentive (STI).
401(k) plan with company match.
Short-term disability coverage.
Paid time off and holidays.
Employee Stock Purchase Plan.
Employee Assistance Program.
Eligible employees may have access to a Non-qualified Retirement Plan Supplement and Capital Accumulation Plan, subject to IRS minimum earnings requirements.