Staff Data Scientist

Job Description

Our Opportunity:

Do you want to build a model that impacts the company’s bottom line? Do you want to see how your ideas, pipelines, architecture, and experiments affect top-level decision-makers? If so, the Chewy Marketing & Science team is hiring! The team uses AI, machine learning, statistics, and business econometrics techniques to understand and serve the needs of our pet parents. As part of the Marketing Science teams, you will have ample opportunities to solve numerous business problems for marketing and existing Chewy customers. Our team has single-threaded ownership to make data science and AI products powered by ML models, Generative AI, econometric models, causal inference, forecasting, and non-linear optimization. We are hiring a Staff Data Scientist in Bellevue, WA, Boston, MA, or Plantation, FL. In this position, you will work on all stages of model development, from idea, analysis, architecture, pipeline, tuning, experimentation, and feedback loop. This team’s MLEs and data scientists focus on learning and working together to deploy the model to production and advance our modeling technique. Join our high-achieving team!

What You’ll Do:

• You will partner with peer MLEs, Program Managers, Marketers, Finance, and top engineers at Chewy. 
• You will be responsible for science projects from idea to offline evaluation to deployment, to experiment, to feedback, to model improvements for not only your science projects. 
• Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to identify them systematically, and explaining why they are reasonable or identifying fixes. 
• Developing generative AI solutions for various marketing applications.
• Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, and sharing insights and recommendations.
• Work with a team of incredible people passionate about data science, machine learning, AI, search & personalization. 

What You’ll Need:

• An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Physics, Data Science, or a related field or 5+ years’ experience designing optimization and machine learning solutions for large-scale applications.     
• Ability to understand and apply advanced mathematics and DS methodologies. 
• Experience in building distributed pipelines, tuning, optimizing, and evaluating.
• Experience with standard ML and statistical techniques including Predictive Models (Time Series, Regression, etc.), Classification, Forecasting etc.
• Experience with modern LLM frameworks (e.g., LangChain, LlamaIndex) and LLM architectures and techniques (e.g., RAG, agents, text-to-SQL)
• Strong programming skills in Python and experience with ML frameworks
• Ability to thrive in ambiguous situations and transform open-ended problems into structured solutions
• Excellence in communicating technical concepts to non-technical stakeholders

Bonus (if applicable):

• Experience with causal inference. If not, we’ll teach you. 
• Experience with at least one cloud services provider(AWS, GCP, Azure, etc.).
• Experience with ML framework, e.g., Databricks.