Who we are:

The Supply Chain Planning and Analytics team works cross-functionally across the Wayfair Operations group to tackle complex and high-visibility operational planning and long-term strategy problems. To do this, we use analytics, structured process design, and technology to frame the future supply-chain business strategy for Wayfair and drive operational decision making. As a team, we create innovative sales and operations planning systems to maximize delivery speed and minimize cost both Wayfair and its 8000+ suppliers.  We also act as internal consultants influencing a wide array of decisions including transportation optimization, forecasting, fulfillment center and middle mile facility footprint design, inventory optimization, and capacity planning.   

What you will do:

  • Use analytical and quantitative skills to work with large and complex data sets, analyze ill-defined questions, build decision-support tools, and develop recommendations to guide business decisions
  • Serve as the technical lead for forecasting and demand modeling projects to create state-of-the-art solutions that will enhance the efficiency of North American and European supply chain networks
  • Conduct big data analysis using Python, SQL, and Hive and create scalable forecasting algorithms using time series and mathematical modeling to support capacity planning and staffing decisions at our WDN facilities and fulfillment centers, and industrial engineering decisions
  • Provide analysis using quantitative modeling tools to benchmark existing forecasts/processes, new model requirements, as well as to identify opportunities for improvement
  • Build predictive and other ad-hoc models as per the business requirements and build forecasts at various granularities across multiple channels and geographies
  • Work closely with OPI, BI, and Engineering teams to enhance prototypes, build visualizations for executive level KPI reporting, and implement solutions in production environment
  • Partner with various business stakeholders to identify key factors and requirements for each project and get buy-in for project methodology
  • Communicate findings with colleagues from computer science, operations research, and business backgrounds

Who you are:

  • A highly analytical individual who can give structure to complex and often ambiguous data and modeling problems
  • MS/PhD in a quantitative field (Engineering, Operations Research, Mathematics, Economics) with a strong academic record
  • 2+ years professional work experience with statistical and predictive modeling, demand forecasting, and time series analysis using ARIMA, Holt-Winters, and Bayesian models
  • Strong coding skills in Python to write scalable and production level code
  • Experience with big data analysis tools and data engineering using SQL, Hive, etc.
  • Experience with distributed version-control using Git and knowledge of visualization tools (Tableau, Power BI, etc.)
  • Passionate about tackling complex supply-chain business problems from problem definition and business-case development to implementation
  • A natural team player who is willing to help other analysts and business stakeholders with their data and modeling needs
  • Eagerness to present business cases and analysis insights to peers, stakeholders, and senior leadership
  • Strong written and verbal communication skills including the ability to translate sophisticated analyses into a logical, convincing business narrative
  • Affinity for working with data and resourcefulness in situations where clean data and/or complete information is not available

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