Associate Director, Forecasting Analytics

Associate Director, SIOP Forecasting Analytics

Role Overview

The AI & Analytics Leader – Forecasting will own the end-to-end design, development, and scaling of advanced forecasting solutions leveraging AI/ML. This role will drive predictive intelligence across SIOP, demand planning, inventory optimization, and aftermarket growth, translating business problems into scalable AI products.

Key Responsibilities

AI Strategy & Vision

• Define the AI roadmap for forecasting across regions and business units
• Identify high-value use cases (demand sensing, pricing elasticity, parts forecasting, supply optimization)
• Align AI initiatives with enterprise value levers (revenue growth, cost optimization, service levels)

Model Development & Deployment

• Design and deploy advanced models (time-series, probabilistic forecasting, causal ML, GenAI copilots)
• Lead experimentation frameworks (A/B testing, backtesting, scenario simulations)
• Ensure scalable deployment via MLOps pipelines

Productization of AI Solutions

• Convert models into reusable AI products (forecasting engines, APIs, copilots)
• Work closely with product managers to define features, roadmaps, and adoption strategies
• Drive standardization across markets while enabling localization

Business Impact & Value Realization

• Quantify and track value (forecast accuracy improvement, inventory reduction, revenue uplift)
• Partner with Finance and business teams for value baselining and realization
• Continuously optimize models based on performance and feedback loops

Stakeholder & Team Leadership

• Collaborate with SIOP leaders, supply chain teams, and digital leadership
• Lead a team of data scientists, ML engineers, and analysts
• Act as a thought leader in AI within the organization

Key Skills & Qualifications

• 10–15 years experience in AI/ML, with strong focus on forecasting or supply chain analytics
• Deep expertise in time-series forecasting, ML, and optimization techniques
• Experience with MLOps, cloud platforms (GCP/AWS/Azure), and data ecosystems
• Strong business acumen in supply chain/SIOP processes
• Proven ability to drive AI adoption at scale

Success Metrics

• Forecast accuracy improvement (%)
• Inventory reduction / working capital impact
• Revenue uplift from AI-driven insights
• Adoption rate of AI products across BUs

Pay Range: