Job Description


Demand Planning Manager, Forecasting Manager

View: 184

Company: Michael Page
Contract: PERM
Location: Cranbury, United States


  • ERP Experience

  • NYC or NJ

About Our Client

Home Interior Goods

Job Description

MPI does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or based on an individual's status in any group or class protected by applicable federal, state or local law. MPI encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants.

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.

The Successful Applicant

Required Qualifications:

  • Education: Bachelor of Science in Industrial Engineering, Operations Research, Mathematics, Statistics, Data Science, or similar quantitative discipline; Master's Degree a plus
  • A minimum of 5 years' experience in a demand planning/forecasting role at a consumer product retailer. Experience in demand planning for e-commerce a plus
  • Proficiency with SQL (T-SQL preferred), generating advanced queries to support ongoing data analysis efforts and modeling

Additional:

  • Advanced analytical skills in Microsoft Excel (complex functions, pivot tables, conditional formatting required, get & transform/power pivots, macros a plus)
  • Programming experience (Python, R, VBA)
  • Experience in visualization tools (SSRS, Power BI)
  • Experience applying data science concepts: algorithm development, data mining/web-scraping, machine learning, etc. to produce best-in-class mathematical models

  • Capability to multitask in a fast-paced environment.
  • Excellent written and verbal communication skills

What's on Offer

As a member of our team, you will be provided with a package that includes a competitive base salary, performance bonus, 401k matching and full healthcare benefits.

 
 
 
 
 





More Info / Apply

(external link to recruiter web page)








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News & Trends
 

Last update 6 Feb 2021
January PMI hits record high amid strong client demand
   Source: Markit US Manufacturing PMI   -  IHS Markit
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