Research Scientist II

Chewy - Boston, MA

Full-time - Mid Level

Boston, MA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

Chewy is seeking a Research Scientist II to join the Supply Chain Outbound Science team, focusing on optimizing supply chain frameworks through machine learning and optimization techniques. The role involves developing and implementing models to enhance outbound fulfillment processes, ensuring adaptability to the complexities of supply chain systems. The position is integral to driving transformation towards ML-based replenishment models, with a strong emphasis on collaboration across various organizational stakeholders.

Responsibilities

• Develop and implement models and solutions to solve complex supply chain problems using optimization, machine learning, and AI techniques.
• Deep dive into large supply chain data to explain changes, develop insights, and provide recommendations.
• Collaborate with stakeholders across organizations to understand business requirements and translate them into technical specifications for models and algorithms.
• Implement process improvement initiatives that drive improvements to metrics and streamline the Supply Chain.
• Communicate technical concepts and results to non-technical stakeholders in a clear and concise manner.

Requirements

• An advanced degree (M.S., PhD preferred) in Data Science, Operations Research, Applied Mathematics, or related fields.
• Strong background in Optimization and machine learning with practical experience in developing and deploying models in cloud environments like AWS, Azure, Google Cloud, etc.
• Two years of working experience on solving supply chain business problems is highly preferred.
• Prior experience working with deep learning models like NNs, CNNs, LSTM, etc., and RL models is highly preferred.
• Proficiency in Python coding including ML libraries.
• Proficiency in solving optimization problems using Gurobi, Xpress, or CPLEX.
• Ability to use collaborative programming tools (Git, Confluence, etc.).
• Ability to translate complex data sets and research into simple business recommendations.
• Ability to manage multiple projects and prioritize competing requirements.