Research Scientist III

Chewy Chewy · Retail · Bellevue, WA +1

Research Scientist III at Chewy focused on developing and implementing ML-based replenishment models to optimize supply chain outbound fulfillment. Requires a strong background in optimization and machine learning, with experience in cloud environments and deep learning/RL models.

What you'd actually do

  1. Develop and implement models and solutions to solve complex supply chain problems using optimization, machine learning techniques.
  2. Deep dive large supply chain data to explain change, develop insights, and provide recommendations.
  3. Work with collaborators across organizations (with Inbound, S&OP, Transportation, and Supply Planning) to understand business requirements and translate them into technical specifications for models and algorithms.
  4. Implement process improvement initiatives that drive improvements to the metrics and streamline the Supply Chain.
  5. Communicate technical concepts and results to non-technical stakeholders in a clear and concise manner.

Skills

Required

  • Python coding including ML libraries
  • solving optimization problem using library Gurobi, Xpress, CPLEX
  • collaborative programming tools (Git, Confluence, etc.)
  • translate complex data sets and research into simple business recommendations
  • manage multiple projects and prioritize competing requirements

Nice to have

  • M.S., PhD (preferred), or equivalent experience) in Data Science, Operations Research, Applied Mathematics, or related fields.
  • developing and deploying models in cloud environments like AWS, Azure, Google cloud, etc.
  • 2+ years working experience on solving supply-chain business problem is highly preferred.
  • deep learning models like NNs, CNNs, LSTM, etc., and RL models, highly preferred.

What the JD emphasized

  • ML-based replenishment models
  • optimize our outbound fulfillment
  • supply chain problems
  • supply chain data
  • supply chain systems
  • supply chain business problem

Other signals

  • ML-based replenishment models
  • optimize our outbound fulfillment
  • develop and implement models and solutions
  • deep dive large supply chain data
  • optimization, machine learning techniques