Chewy is looking to redesign and optimize its supply chain optimization frameworks from the ground up to ensure adaptability to constant changes and complexity in its supply chain systems, aiming to achieve large-scale savings and make a significant business impact.
Requirements
- Strong background in machine learning with practical experience in developing and deploying machine learning models in cloud environments like AWS, Azure, Google cloud, etc.
- Prior experience working with deep learning models like NNs, CNNs, LSTM, etc., and RL models, highly preferred.
- Proficiency in Python ML libraries such as TensorFlow, PyTorch, PySpark, etc.
- Knowledge and experience in supply chain, highly preferred.
- Ability to use collaborative programming tools (Git, Confluence, etc.)
- Ability to translate complex data sets and research into simple business recommendations.
Responsibilities
- Develop and implement models and solutions to solve complex supply chain problems using machine learning techniques and other relevant artificial intelligence (AI) techniques.
- Deep dive large supply chain data to explain change, develop insights, and provide recommendations.
- Work with stakeholders across organizations (with Demand Planning, S&OP, Transportation, and Supply Planning) to understand business requirements and translate them into technical specifications for models and algorithms.
- Implement process improvement initiatives that drive improvements to the metrics and streamline the Supply Chain.
- Communicate technical concepts and results to non-technical stakeholders in a clear and concise manner.
Other
- An advanced degree (M.S., PhD (preferred), or equivalent experience) in Computer Science, Operations Research, Applied Mathematics, or related fields.
- Ability to manage multiple projects and prioritize competing requirements.
- Unlimited PTO, subject to manager approval.
- Team members will receive six paid holidays per year.
- Team members may be eligible for paid sick and family leave in compliance with applicable state and local regulations.
