Sr Manufacturing AI/Data Science Engineer at MiniMed Group in Northridge, CA

Job description

We anticipate the application window for this opening will close on - 9 Nov 2026 At MiniMed, you can begin a lifelong career of exploration and innovation, while helping make a difference in the lives of people living with diabetes around the globe. You'll lead with purpose, breaking down barriers to innovation for a more connected, compassionate world. About the Role Must have Manufacturing experience!!! Candidates can be either of our Northridge CA office or our St. Louis Park MN office. Must be onsite 3 days per week/2 day remote. MiniMed is seeking a Senior Manufacturing AI/Data Science Engineer to join our Data Science team in a dedicated capacity supporting manufacturing, supply chain, operations, and new product introduction (NPI) functions. This role is responsible for accelerating the evolution of our cloud data infrastructure for manufacturing data sources, solidifying trusted operational metrics, supporting root cause investigations with advanced analytics, and progressively delivering predictive and AI-driven solutions that improve how we design, build, and deliver our products. The ideal candidate is a technically strong data scientist with experience in supply-chain, manufacturing, or a related industry who thrives in complex, cross-functional environments. Candidates may work from either our Northridge, CA or St. Louis Park, MN office and must be onsite three days per week, with two remote days. MiniMed is seeking a Senior Manufacturing AI/Data Science Engineer who combines deep manufacturing knowledge with strong analytics and data science capabilities. This role will apply statistics, advanced analytics, machine learning, and emerging AI technologies to solve complex challenges across manufacturing, quality, supply chain, operations, and new product introduction. The successful candidate will work closely with manufacturing and cross-functional partners to investigate process and quality issues, improve manufacturing data and operational metrics, and deliver analytical solutions that improve product quality, process performance, operational efficiency, and decision-making. The role will also help identify and implement practical AI opportunities based on clearly defined manufacturing needs, data readiness, regulatory considerations, and measurable business value. The ideal candidate has significant experience working in a manufacturing environment and a proven history of applying analytics, statistics, data science, or AI to solve manufacturing and operational challenges. They understand how products, processes, equipment, materials, quality systems, and operational decisions interact and can translate manufacturing problems into effective, data-driven solutions. Essential Duties and Responsibilities Serve as a trusted manufacturing analytics partner to manufacturing engineering, operations, quality, supply chain, and NPI teams, developing a strong understanding of production processes, equipment, materials, data flows, and key performance drivers. Lead and support data-driven investigations into yield loss, scrap, defects, equipment performance, downtime, process variation, throughput, capacity, cycle time, and other manufacturing and quality challenges. Apply statistical and analytical methods to identify sources of variation, evaluate potential causes, quantify relationships, and accelerate the resolution of complex manufacturing problems. Partner with data engineering, IT, and manufacturing systems teams to improve the availability, context, quality, reliability, and governance of manufacturing data. Apply appropriate methods such as statistical process control, process capability analysis, design of experiments, regression, multivariate analysis, time-series analysis, predictive modeling, machine learning, computer vision, or generative AI based on the specific manufacturing problem. Identify practical opportunities to apply AI and machine learning across manufacturing, quality, supply chain, operations,