Associate Pricing Manager - Pricing Strategy & Analytics

  • Department -
  • Team -
  • Employment Type -
  • Position -
  • Requisition GH1291504

What you'll do at

About Walmart eCommerce

Walmart eCommerce is rapidly innovating to evolve and define the future state of shopping. With some of the brightest minds in product, technology, merchandising, marketing, supply chain and more, we are reimagining the intersection of digital and physical shopping to help achieve that mission. Backed by the world’s largest retailer, Walmart eCommerce is a growing family of brands including Walmart, Jet, Hayneedle, Moosejaw,, and more. And we’re just getting started.

About the Role

We're growing our Pricing team, where we combine an understanding of technology, economics, and customer behavior to develop dynamic pricing algorithms and create structures and incentives to cut hidden costs out of e-commerce pricing. In this position, you will have the opportunity to develop your analytical and technical skills and shape the e-commerce landscape as you work with some of the largest datasets in the world and provide insights to guide critical business decisions.

This role will work across the broader Walmart eCommerce portfolio focusing on Jet and


  • 3+ years of experience in a data / analytics role
  • Bachelor’s degree from a rigorous undergraduate program with demonstrated high academic achievement – Statistics, Computer Science, Math, Physics, or other technical fields preferred
  • Understanding of big data technologies (MapReduce, Hadoop, Spark, Hive) and ETL
  • Working knowledge of SQL, Python, R

You will

  • Work across Retail, Product, Data Science and Engineering, using data insights to drive our pricing algorithms and evaluate their impact on the performance of the retail business
  • Continuously evaluate the performance of our pricing strategy by designing, building and maintaining scalable solutions for monitoring and reporting
  • Develop an in-depth understanding of data across and its affiliates, applying best practices in data integrity, analysis, and documentation
  • Write efficient code, periodically identify opportunities for optimization, efficiently detect patterns and outliers, analyze key performance metrics
  • Design and drive experiments and A/B testing

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