Demand Planning + Replenishment Forecasting Manager

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Description

Responsibilities:

• Develop effective forecast models based on industry trends and demand patterns.
• Present forecast and inventory estimations to management on an ongoing basis
• Partner with operations teams to execute replenishment strategy

• Track forecast accuracy and conduct monthly forecast maintenance - address demand-related issues in a timely and effective manner.

• Monitor and report on important changes in sales forecasts, budgets, and business strategies

• Support management with ad-hoc risk assessments and mitigation activities

Modeling/Analysis:

• Develop mathematical models to build data-driven decision-making systems for inventory optimization and allocation, improving Supply Chain performance
• Improve replenishment ordering model with programming languages and version control systems (e.g., SQL, R, Python, Git). Consolidate big data sets with millions of records, determine the optimal inventory order quantity to balance customer experience and company operating costs
• Create mixed integer programming optimization models to estimate right service levels to drive profitability and customer experience with most accurate inventory.
• Develop advanced replenishment and safety stock models to drive the right target Inventory across assortments to improve customer Service level, Turns etc.
• Build mathematical models in R/Python to systematically round up the order quantities generated by the replenishment system up to the Minimum Order Quantity (MOQ) thresholds for the vendors. The model should optimize the order quantity recommendation for the high velocity items and not over order for lower velocity items.
• Build mathematical models in R/Python to optimize inbound shipments from supplier to fulfillment centers and optimize order frequency to create the most efficient flow of products through the supply chain.
• Perform analyses to generate insights and actionable recommendations to leadership to solve immediate business questions and make strategic decisions for future supply chain planning
• Develop advanced forecast models using Machine Learning concepts to capture different demand patterns (seasonality, event driven sales, price driven sales, etc) and drive improvements in forecasting models to improve accuracy of forecast
• Leverage existing software packages and provide guidance on additional software needs to build out capabilities.

Systems:

• Design and build scalable data pipelines across data warehouses (SQL Server, BI software packages, etc.) using SQL to efficiently maintain years of historical data and allow analysts to easily access the data for analyses and modeling
• Leverage virtual machines to productionize scripts to efficiently execute monthly purchase orders, fulfilling inventory across the entire Global eCommerce network
• Develop normalized databases as needed to store structured /transactional data efficiently; in addition to developing big data solutions using Google Big query to support unstructured data
• Develop data visualization and reports for key metrics in Supply Chain inventory management: Item In-stock, Inventory Turns, Purchase Order Visibility, Forecasts, etc. These reports help executive leadership to track business performance and drives process improvement initiatives
• Develop and own Business Intelligence tools which include SSRS/Power BI Dashboards, automated report creation and distribution, Online Analytical Processing (OLAP) solutions like SSAS.