Director, Decision Science & AI/ML

3M • Maplewood, MN

2d • $266,001 - $325,112 • Onsite

About The Position

As Director of Decision Science & AI/ML, you will define and lead the next generation of enterprise data and AI/ML capabilities at 3M. You will build and scale intelligent data products and knowledge graphs that move the company beyond static reporting and insights toward contextual, AI-driven decision intelligence. This role offers the opportunity to shape how data, AI, and decision intelligence transform a global enterprise. You will lead the design and delivery of modern solutions that combine data engineering, AI/ML, and semantic data foundations to power business innovation, operational excellence, and enterprise decision-making. Leading the strategic direction and execution of Intelligent data products initiatives across the 3M. This role will focus on harnessing the power of data and AI/ML, to drive business innovation and operational excellence across the company. This role requires a strategic thinker with a deep understanding of technology and its application in business contexts.

Requirements

• Bachelor's degree in computer science, Data Science, AI/ML (completed and verified prior to start)
• Ten (10) years of experience leading data, analytics, AI/ML initiatives in a private, public, government, or military environment
• Five (5) years of deep expertise in designing, architecting and delivering data engineering, ML platforms, and generative AI ecosystems

Nice To Haves

• Data Lakehouse architectures, Graph Data Architectures and cloud‑native engineering.
• Intelligent data products or data-as-a-product programs including Knowledge graphs and semantic data layers
• Generative AI solutions, with preferred experience building conversational data analysis solutions
• AI driven 360 degree solutions such as Customer 360, Supplier
• Predictive AI/ML Models in Marketing, Supply Chain and Finance domains (Customer Behavior Predictions, Demand Planning, Financial Forecasting, Customer Lifetime Value, Customer Churn etc)
• AI Ops and ML Ops managing the full lifecycle of AI/ML Models including Data Drift, Model Drift and Model Risk Management
• Enterprise data catalog and metadata platforms

Responsibilities

• Next-Gen Data Product Strategy: Lead the transition from descriptive analytics to Decision Science, building intelligent products that provide proactive recommendations across the enterprise.
• Conversational Analytics: Drive the development of Conversational Data Analysis solutions that allow users to query data via natural language, moving away from rigid dashboarding to fluid, role-based insights.
• Predictive Modeling: Drive the roadmap of predictive models, tools and utilities that will be leveraged by AI Agents to drive automated decisions in business processes across Commercial, Operational and Enterprise functions.
• Apply Decision Science: Implement decision science frameworks to support strategic, operational, and financial decision-making, enabling predictive and prescriptive insights that drive measurable business outcomes.
• Dynamic Persona-Based Insights: Develop insight systems that deliver real-time, context-aware intelligence tailored to specific roles—from executives to frontline operators.
• Semantic Data Architecture: Establish robust enterprise capabilities in Data Cataloging, Metadata Management, and Semantic Data Fabric architecture to ensure high-fidelity data is ready for AI/ML consumption.
• Knowledge Graphs & Ontologies: Build and scale enterprise Knowledge Graphs and Business Ontologies to unify structured and unstructured data, enabling deep reasoning and power context aware enterprise search.
• AI Consumption Layer: Build context-aware enterprise data layers, ensuring data is ready for consumption by advanced AI models and automation tools across R&D, Manufacturing, Supply Chain, and Commercial functions.
• Technical & Platform Collaboration: specific collaboration with the Data Platform, Data Engineering, AI Engineering, Product Management, Master Data Management (MDM), and Data Observability teams. You will ensure alignment on architectural standards, unified data governance, and operational reliability.
• Adoption & Change Management: Drive the adoption of intelligent insights across the value chain—including Product Development, Portfolio Management, Operations, Sales, and Customer Experience—serving as a strategic advisor to senior leadership.
• Robust Governance: Establish governance models for data quality, model reliability, trust scores, semantic consistency, and Responsible AI.

Benefits

• 3M offers many programs to help you live your best life – both physically and financially.
• To ensure competitive pay and benefits, 3M regularly benchmarks with other companies that are comparable in size and scope.
• Medical, Dental & Vision, Health Savings Accounts, Health Care & Dependent Care Flexible Spending Accounts, Disability Benefits, Life Insurance, Voluntary Benefits, Paid Absences and Retirement Benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Director