Job Description

At Chewy, it is our mission to become the most trusted and convenient online destination for pet parents and our partners vets and service providers alike. Our success is measured by the happiness of the people and pets we serve, not simply by the amount of pet supplies we deliver. That’s why we continue to think of outside-the-Chewy-box ways to delight, surprise, and thank our loyal pet lovers!

Our Opportunity:

Chewy is seeking a  Data Scientist to join our Inbound Tech team in Bellevue WA. The team focuses on technology improvements in the inbound supply chain space, ranging from transportation decisions to informing inbound labor planning. You will partner daily with your data science, software engineering, business, and product teammates/partners. This role will act as an Individual Contributor, Thought Leader, and Mentor. You will design, test, and implement solutions, influence roadmaps, and guide teammates and initiatives.

As part of the data science team at Chewy, you will have the opportunity to provide structure to business problems for new and existing Chewy customers by applying data science principles to design, test, implement, and develop data-based solutions, including reporting, auditing, and preparing large databases for statistical analysis.

You will develop new and improve existing science models; partner with engineering to deploy those models; perform analysis and scoping of new opportunities; analyze data in ad-hoc and planned analyses to understand where we have opportunities to use science to make a difference for Chewy’s Pet Parents. You are comfortable partnering with a software engineer to deploy a model.

What You’ll Do:

• Develop new and improve existing models and solutions to solve complex supply chain problems using machine learning, optimization, and relevant simulation or artificial intelligence (AI) techniques

• Create effective data science framework to optimize and deliver results by reducing computational complexity, increasing the accuracy of models, and improving business metrics


• Monitor and improve the performance of data solutions, identifying bottlenecks, optimizing data processing speeds, and ensuring ease of maintenance and scalability


• Research and remain current on machine learning and optimization techniques

• Partner with engineering to deploy science models


• Perform analyses to troubleshoot performance and understand where we have opportunities to improve.


• Establish strong working relationships at all organizational levels across different functional teams. You may work with multiple teams and systems across Fulfillment, Supply Chain, and Finance.


• Communicate project status, risks, and solutions to team and partners in a clear and concise way.

What You’ll Need:

• 3+ years of hands-on experience in developing and deploying optimization and/or predictive models in fast-paced environment 


• Advanced degree (MS or PhD) in Industrial Engineering, Operations Research, Statistics, Applied Mathematics, or equivalent quantitative fields such as Engineering, Computer Science with a background in both time series and machine learning 


• Understanding of "good enough": science models and analysis don’t have to be perfect to provide critically beneficial insights 


• Proficiency in SQL and experience with programming languages such as Python, Java, R, or equivalent


• Track record dealing with complex and solving and ambiguous problems that drive business value.


• Ability to work with large datasets using distributed computing tools 


• Excellent verbal and written communication skills. Must be able to tailor details and complexity to level of the audience.


• Approximately 4% domestic travel required.


• The position is eligible for the Employee Referral Program.

Nice to Have:

• Experience in a fulfillment or logistics or e-commerce environment.


• Experience with Amazon Web Services tools such as Redshift, Snowflake, SageMaker or other similar platforms 


• Experience in building simulations or optimization models for supply chain.


• Experience with data visualization tools and packages (Tableau or similar)

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