Data scientist
Our Opportunity
Are you passionate about using AI and data science to make a real impact? Do you get excited by the idea of seeing your models, insights, and prototypes directly influence company strategy? If so, we’d love for you to join the Chewy Marketing Science team! At Chewy, our mission is simple: to make pet parenting easier and more joyful. Our Marketing Science team plays a key role in that mission by applying machine learning, AI, and statistical modeling to better understand and serve our customers—the millions of pet parents who trust Chewy every day. As a Data Scientist III On Our Team, You’ll Work On Projects That Span Measurement, Optimization, And Personalization, Helping To Unlock Smarter And More Meaningful Ways To Connect With Customers. You’ll Have The Chance To- Build and deploy data-driven solutions that influence real business decisions
- Prototype innovative AI and ML approaches that create measurable impact
- Collaborate with dedicated peers—data scientists, engineers, and marketers—who value learning, creativity, and inclusivity
- Work with ground breaking technology in an environment that encourages experimentation and continuous growth
- Lead end-to-end data science projects—from idea generation and offline evaluation to deployment, experimentation, feedback loops, and continuous model improvement.
- Build, evaluate, and deploy predictive, statistical, and machine learning models (e.g., regression, forecasting, uplift, attribution, causal inference, deep learning)
- Formalize assumptions about model behavior, define and detect outliers systematically, and implement fixes or improvements where needed.
- Partner with marketing team members to identify, scope, and prioritize AI and data science opportunities that create measurable business impact.
- Build internal AI copilots and assistants that enhance productivity, automate repetitive workflows, and accelerate campaign execution.
- Stay ahead of industry and technology trends to anticipate emerging opportunities in AI and e-commerce.
- Communicate insights and recommendations clearly—both verbally and in writing—to audiences with varying technical expertise.
- Advanced degree (M.S., Ph.D., or equivalent experience) in Data Science, Statistics, Applied Mathematics, Computer Science, Physics, or a related field, or 4+ years of experience designing optimization and machine learning solutions at scale.
- Strong foundation in machine learning and statistical methods, including Bayesian inference, regression, classification, forecasting, time series, causal inference, and machine learning techniques such as tree-based models (e.g., XGBoost, Random Forests), neural networks, and clustering methods.
- Ability to understand and apply advanced mathematics and data science methodologies to solve complex business problems.
- Hands-on expertise with LLMs and Generative AI frameworks and LLM ecosystems (g., LangChain, Hugging Face, OpenAI, Anthropic, vector databases).
- Proficiency in Python (and ideally SQL/ML pipelines) for building proof-of-concepts and deploying production-ready solutions.
- Strong ability to translate business needs into AI and data science opportunities, with knowledge of marketing workflows, customer data, and campaign lifecycles.
- Proven ability to prototype quickly, iterate through experimentation, and operationalize models into production.
- Strong eye for business and problem-solving skills - the ability to thrive in ambiguous, fast-paced environments, structuring open-ended problems into actionable solutions.
- Excellent communication skills, with the ability to convey technical concepts to both technical and non-technical partners
- An AI-native mindset—curious, creative, and eager to harness the latest AI tools to accelerate marketing impact.
- Expertise in Bayesian statistics and hierarchical modeling
- Experience with marketing measurement and optimization, including budget allocation, channel mix modeling, and campaign performance optimization.
- Exposure to reinforcement learning or agentic AI systems for marketing optimization.
- Experience with at least one cloud services provider(AWS, GCP, Azure, etc.).
- Experience with ML platforms, e.g., Databricks.
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