Responsibilites

• Strategic Planning and Risk Mitigation: Drive clarity and understanding of requirements to achieve operational plans, including promotions, sales resources, collaborative planning, forecasting, replenishment (CPFR), budget, and engineering changes. Assess and mitigate potential risks and issues to ensure alignment with business objectives.
• Model Research and Development: Research and develop production-grade models for operations research, inventory optimization, forecasting, anomaly detection, and clustering. Apply statistical, machine learning, and optimization techniques to address complex supply chain challenges and drive impactful business outcomes.
• Data Management and Feature Engineering: Manage large volumes of structured and unstructured data, creating improved processes for data collection, management, and analysis. Drive feature engineering and selection to enhance model performance for forecasting, inventory optimization, and demand planning.
• Optimization and Solver Expertise: Leverage optimization modeling, operations research techniques, and solvers to develop actionable solutions for supply chain challenges, including inventory management, replenishment, and capacity planning. Consistently apply algorithmic techniques to optimize solutions for real-world business scenarios.
• Collaboration and Innovation: Lead cross-functional collaboration to identify opportunities for state-of-the-art algorithm application in solving supply chain and demand planning problems. Guide teams in using data-driven insights to uncover trends and recommend strategies for optimization.
• Forecasting and Demand Planning: Oversee the creation and refinement of short- and long-term demand forecasts. Analyze forecast accuracy metrics, identify potential sources of error, and implement advanced statistical models to improve forecast precision and reliability.
• Advanced Analysis and Troubleshooting: Modify and enhance statistical and machine learning tools for evaluating optimization and inventory models. Solve challenging problems related to data quality, model performance, and ambiguous business requirements by leveraging expertise in operations research and supply chain management.
• Communication and Leadership: Present analytical findings and business insights to stakeholders and senior leadership. Serve as a mentor to team members, providing guidance on the application of optimization and machine learning techniques within a supply chain context.
• Governance and Process Improvement: Advocate for continuous improvement by leading governance processes and fostering cross-group collaboration to address current and future supply chain needs. Ensure the incorporation of best practices and business drivers into operational plans.