Associate Director, Forecasting Analytics

Carrier seeks an Associate Director to lead AI/ML forecasting initiatives across supply chain operations, driving predictive intelligence and scalable AI product development.

This role is responsible for the full lifecycle of advanced forecasting solutions, from initial design through to scaling. The position focuses on translating complex business challenges into robust AI products that enhance demand planning, inventory management, and overall supply chain intelligence.

Responsibilities

• Establish the strategic direction for AI-driven forecasting across various global regions and business units.
• Pinpoint high-impact opportunities such as demand sensing, pricing elasticity analysis, parts forecasting, and supply optimization.
• Ensure AI projects align with key business objectives like revenue growth, cost reduction, and service level improvements.
• Develop and implement sophisticated models including time-series analysis, probabilistic forecasting, causal ML, and GenAI copilots.
• Oversee experimentation frameworks, including A/B testing, backtesting, and scenario simulations.
• Guarantee scalable model deployment through MLOps pipelines.
• Transform models into reusable AI products, such as forecasting engines, APIs, and copilots.
• Collaborate with product managers to define features, roadmaps, and adoption strategies.
• Drive standardization across markets while enabling localization.
• 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.

Requirements

• 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