Manager MP&L - AI and Digital Transformation
Key Responsibilities
- Develop and execute the AI and Innovation roadmap for MP&L department aligned with enterprise objectives.
- Identify, evaluate and implement high-impact projects where AI/ML, Generative AI, Computer Vision, IoT, and Digital Twins can optimize inventory levels, Improve BOM Health, reduce freight costs, mitigate supplier risks, and streamline material handling and improving operational performance.
- Establish metrics and key performance indicators (KPIs) to evaluate the business value, ROI, and operational efficiency gains of deployed AI solutions.
- Champion innovation by evaluating emerging technologies, piloting new concepts, and scaling successful solutions across the organization.
- Develop predictive and prescriptive analytics for demand forecasting, inventory optimization, material shortage prediction, supplier risk management, and logistics optimization.
- Collaborate with Supply Chain, Purchasing, PD, Manufacturing, Quality, Finance IT, GDIA and external partners to deliver innovative and scalable solutions.
- Drive utilizing the governance forums to monitor innovation initiatives and AI solutions, track business benefits and drive continuous improvement.
- Foster an innovation culture by promoting idea generation, facilitating innovation workshops, sharing best practices, and building AI and digital capabilities across the function.
- Serve as the MP&L liaison to external innovation ecosystems, including tech startups, university research labs, supply chain / logistics software vendors, and industry consortiums.
- Drive change management and training initiatives to foster a data-driven, innovation-first culture within the global MP&L organization.
- Apply Lean / Six Sigma principles alongside digital tools to eliminate waste, lower carbon footprints (sustainable logistics), and enhance supply chain resilience.
Technical Skills & Knowledge
- AI & Analytics: Practical understanding of machine learning algorithms (regression, classification, clustering, time-series forecasting), optimization modelling, deep learning, computer vision, and Generative AI applications.
- Supply Chain Systems: Expertise in modern ERP systems (SAP S/4HANA), Warehouse Management Systems (WMS), Transportation Management Systems (TMS), and Material Requirements Planning (MRP).
- Data & Cloud Platforms: Familiarity with cloud environments (AWS, Azure, or GCP), data visualization tools (Tableau, Power BI), and data processing architectures (SQL, Python/R capabilities).
- Emerging Tech: Exposure to IoT sensors, RFID tracking, Digital Twin simulation tools, Autonomous Mobile Robots (AMRs), and edge AI.
Strategic Thinking, Project Management, Stakeholder Management, Change Leadership, and Cross-functional Collaboration Soft Skills & Leadership Competencies
- Strategic Thinking: Ability to translate complex operational challenges into actionable AI technical roadmaps.
- Change Management: Proven ability to influence stakeholders at all levels, from plant floor operators to executive leadership.
- Agile Delivery: Experience working in Agile environments for software and product development.
- Communication : Exceptional storytelling and executive presentation skills with the ability to articulate technical AI concepts in clear business terms.
Qualifications & Experience
- Bachelor's degree in Engineering, Supply Chain, Operations research, Computer Science, Data Analytics, Information Technology, or a related discipline; Master's degree preferred.
- 8–12 years of progressive experience in Supply Chain, Material Planning and Logistics areas.
- Demonstrated experience delivering AI, analytics, automation, or digital transformation initiatives in a manufacturing or automotive environment.
- Proven track record of taking AI/ML or advanced analytics projects from concept to production with measurable business impact.
Preferred Certifications (Plus)
- Certified in Production and Inventory Management or Certified Supply Chain Professional.
- Project Management Professional (PMP).
- Lean Six Sigma Green/Black Belt certification.
- AI/Data Science professional certifications (e.g., Azure AI Engineer, AWS Machine Learning Specialty).
Experience Level Mid Level