Data Scientist II

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!

We are hiring awesome humans, and we hope that includes you!

Are you looking for more than just a job? At Chewy, you’ll find yourself on a career path with other incredible humans, like yourself. You’ll be part of a culture that values everything that you do, who you are, and the goals you have set for your career. We want to give you the opportunity to grow, earn competitive pay, and be happy while you do it. Sounds simple, but we love it.

Your Opportunity:

We are looking for a Data Scientist II within Chewy’s quickly growing Production Planning, Analytics & Technology (PPAT) Science team. This team, a division of the Short-Term Planning group, consists of data and technology experts dedicated to optimizing fulfillment operations, boosting productivity, and reducing costs through precise scientific methods and advanced data analytics. Our mission is to leverage the power of ground breaking science and technology to continuously improve production planning, enable informed decision-making, and deliver innovative technological solutions to the business through interdisciplinary collaboration.

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.  

What You’ll Do:

• Develop and implement models and solutions to solve complex supply chain problems using optimization, machine learning, and relevant simulation or artificial intelligence (AI) techniques
• Research, implement, and test machine learning algorithms and tools to solve data challenges and to improve quality and reliability of data
• Create effective data science framework to optimize and deliver results by reducing computational complexity, increasing the accuracy of models, and improving business metrics.  
• Research and remain current on machine learning and optimization techniques  
• Drive continuous improvement to the delivered assets, bringing in the best new advances using science in the fulfillment operations space 
• 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.
• Identify opportunities for data science to improve current products and practices for business engineering teams.  

What You’ll Need:

• 3+ years of hands-on experience in developing and deploying optimization and/or predictive models in fast-paced environment 
• An 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  
• Demonstrated ability to solve business problems 
• Proficiency in SQL and experience with programming languages such as Python, Java, or R or equivalent experience
• Track record dealing with complex and ambiguous problems that drive business value.
• Ability to work with large datasets using distributed computing tools 
• Excellent verbal and written communication skills and the ability to explain details of complex concepts to non-expert collaborators in a simple and understandable way 

Bonus:

• 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)