Senior Technical Analyst - Replenishment Platform

Hybrid Model (M-TH)

SQL & Python experience required

The Replenishment Platform team is looking for a Technical Analyst to further organizational understanding of performance across an assortment of >25 Million items and to help create strategies which optimize the trade-offs between inventory availability, shipping speed, and supply chain cost.

Who We Are

Wayfair’s Global Demand Planning & Analytics team builds algorithmic solutions to enhance the customer experience, the supplier experience, and internal efficiencies that ultimately drive our bottom line. The team consists of data science/ML/economics experts, ML/software engineers, advanced analysts and product managers; who are responsible for developing and managing global large-scale demand forecasting systems; that power Wayfair’s complex supply chain. Within this broader team, the Catalog Segmentation Strategy and Analytics team helps define how to segment our catalog in a smart way to drive high ROI business outcomes by leveraging nuanced assortment-aware planning & inventory management strategies across our catalog and within each of these segments. The  Replenishment Platform team is looking for a Technical Senior Analyst to further organizational understanding of performance across an assortment of >25 Million items and to help create strategies which optimize the trade-offs between inventory availability, shipping speed, and supply chain cost.

What You’ll Do

• Performing statistical analysis across large data sets and within defined segments to develop performance insights across a myriad of attributes. Leverage these findings to further develop additional segmentation to improve operational efficiencies and business outcomes.
• Creating efficient data structures that can be leveraged across the organization and can be maintained in a dynamic environment. Piping this data to Wayfair backend systems to improve supply chain activity and performance.
• Partnering with our Operations Research team to develop  operational strategies across product segments that optimize business outcomes and improve catalog performance, focusing on achievable and statically feasible approaches.
• Building segment level performance projections to develop holistic views which indicate company wide trajectory across various operational KPI.
• Collaborating with partners in commercial, operations and technology; and ensuring that there is strong alignment between Wayfair’s business objectives and our Data Science driven strategies.
• Developing key metrics and reporting to measure how strategic initiatives are improving Wayfair’s performance and enabling our team to easily identify trends and root causes and develop targeted action plans.
• Partnering with Engineers, Product Managers, and Data Scientists within Forecasting and in adjacent teams to continue to evolve the data science product community at Wayfair.

Who you are:

• A highly analytical individual who can give structure to complex and often ambiguous data and modeling problems
• MS in a quantitative field (Engineering, Operations Research, Mathematics, Economics) with a strong academic record
• Exceptional analytics skill set, including a high degree of comfort / expertise with using SQL, Google Cloud Platform, or other
  relational database technologies on a day-to-day basis with proven track record of insight development leading to action
  •  Experience with statistical programming or scripting languages (Python, R, etc.) 
• Willingness to do hands-on problem solving - including problem definition, prototype development, and work with Engineering to transfer solution to a scalable production environment.
• Passionate about tackling complex supply-chain business problems from problem definition and business-case development to implementation
• Thrives in a fast paced environment with multiple competing priorities and rapid shifts to support the business
• A natural team player who is willing to help other analysts and business stakeholders with their data and modeling needs
• 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