Our Opportunity:

Chewy is looking for a Data Scientist II to join our Merchandising Analytics Team based in Bellevue, WA; Boston, MA; Dania Beach, FL; or Minneapolis, MN. In this role, the Data Scientist II will directly support our Category Management function and be responsible for building and maintaining advanced models that help drive insight into customer behavior with recommendations for action.

In this role, the ideal candidate will operate as a full-stack data scientist, where they will have the opportunity to design and develop the backend ML frameworks best suited for different business problems, build engineering pipelines to streamline the model development process and launch the decision engines that would help automate the ML-powered business solutions. For such efforts, you will closely work with the data science, ML Operations, analytics, and data engineering teams focused on Merchandising problem spaces.

What You'll Do:

• Focusing on the incrementality and the value-creation in everything you do, you will closely work with the stakeholders within the category management teams (Consumables, Premium, Specialty, Hardgoods, etc.). You will transform their ideas, preliminary findings, or analyses, whenever applicable, into rigorous automated ML models driving incremental business value.
• For such transformations, you will guide the teams with the design of experiments, measurement, models, analyses, recommendations, or all. As a data scientist, you will be responsible for making recommendations for experimentation and measurement by researching state-of-art methods, examining, and tuning the current methods with simulations, and build an internal best in class ML pipelines and models to automate the manual translation of free text received from vendors or customers, or transform images sent into usable data to improve the Chewy platform.
• You will be responsible for the full Data Science lifecycle from conception to prototyping, testing, deploying, and measuring the overall business value of the models. In addition, you will periodically develop the model health reports to ensure the integrity of the underlying processes and assumptions. If needed, you will refit the model following the model lifecycle. Using the ML model outputs, you will work with a team of strategic analysts and engineers to triangulate different inputs and optimize the solutions for different business problems.
• You will use data to improve how we make decisions and ultimately, enhance customer experience and drive loyalty. You will surface deep insight hidden in our data lakes and provide tactical and strategic guidance on how to act on findings.
• You will work with the data engineering teams to develop the automated pipelines to perform different stages of the model life cycle (data collection and cleaning, model development and validation, model deployment and scoring, periodic validation and refitting, etc.).

What You'll Need:

• Graduate degree (MS/PhD) in Data Science, Machine Learning, Economics, Statistics, Mathematics, Engineering or related discipline.
• Demonstrated practical knowledge in the areas of machine learning, deep learning, experimentation and testing.
• Advanced proficiency in coding and data analysis using Python or R.
• Advanced proficiency with SQL.
• Proven experience in the design and execution of analytical projects.
• Working knowledge of AWS data toolset (Glue, Athena, Sagemaker, Redshift, etc.).
• Capability of translating ambiguous customer requirements into clear problem definitions and delivering them.
• Excellent verbal and written communication skills. Able to explain details of complex concepts to non-expert stakeholders in a simple understandable way.
• Travel may be required.