Staff, Data Scientist

About The Team

The Discovery Product Analytics team partners closely with the Discovery Product Management, Engineering, and Business teams to build, evaluate, and scale product experiences on discovery and browse page including product design changes and machine learning–powered recommendation that help millions of Walmart customers discover the right products at the right time. We provide the analytical foundations that shape customer relevance, experimentation frameworks, and product roadmap decisions for Walmart’s eCommerce platform.

About The Role

We are seeking a dynamic and experienced Staff, Data Scientist (Individual Contributor). You will be a technical expert driving analytical strategy focused on Home Page, Navigation, Deals and other discovery pages. You will own complex analytical workstreams, design and interpret large-scale experiments, and influence decisions across multiple cross-functional partners. If you’re excited about solving ambiguous, high-impact problems at the intersection of experimentation, product analytics, ML and customer experience, this role is a good fit for you.

Primary Responsibilities

• Product Analytics Leadership: Partner with Product Managers, Engineers, Data Scientists, and UX teams to define success metrics, measurement strategies, and opportunity assessments for product feature enhancements and recommendation algorithms. Translate ambiguous business or product questions into structured analytical approaches that influence prioritization and product direction.
• Deep Customer & Behavioral Analysis: Work closely with engineering and product to build clickstream tracking. Leverage clickstream data, user logs, and customer engagement patterns to understand how customers interact with site features. Partner with personalization data science to increase adoption of personalization algorithms across discovery pages. Conduct funnel analysis, opportunity sizing, cohort analysis, attribution, and retention of Walmart customers.
• Experimentation Strategy & Execution: Design and evaluate large-scale A/B tests and advanced experimentation methods (e.g., quasi-experimental approaches, causal inference). Ensure experiment integrity through appropriate power analysis, guardrail metrics, and thoughtful statistical methodologies. Produce end-to-end experiment readouts with clear conclusions, implications, and directional recommendations grounded in customer behavior.
• ML-Aware & Technical Execution: Use expert-level SQL to analyze large-scale datasets across platforms such as BigQuery, Hive, and Spark to uncover user behavior insights to use for model building and ad-hoc analysis. Develop reproducible analytical pipelines and experiment workflows using Python and PySpark. Familiarity with ML concepts (e.g., predictive modeling using supervised and unsupervised ML methods, dimensionality reduction, clustering). Apply data mining and feature-level diagnostics to identify patterns that impact customer experience or ML performance.
• AI Aware: Use prompt engineering and LLMs to simplify day-to-day work. Hands-on experience to create innovative tools for workflow automation.
• Storytelling & Insight Influence: Deliver compelling, concise narratives that translate analytical findings into product and business implications. Influence product and engineering leaders through data-backed recommendations and clear articulation of trade-offs.
• Cross-Functional Collaboration: Build strong relationships with Product, Engineering, Business and Data Science partners. Serve as a trusted voice who anticipates stakeholder needs, clarifies expectations, facilitates alignment, and drives shared accountability.

Preferred Qualifications

• Bachelor's degree in computer science, Engineering, Mathematics, Statistics, or related field AND 8+ years of experience in product analytics, data science, applied analytics, or experimentation (OR Master’s degree + 6 years).
• Expert-level proficiency with SQL and strong programming skills in Python.
• Hands-on experience designing and analyzing large-scale A/B tests.
• Familiarity with machine learning model concepts and evaluation techniques sufficient to interpret model-driven product behavior and partner effectively with ML teams.
• Demonstrated ability to influence product strategy and partner with senior cross-functional stakeholders.

Success in This Role Looks Like

• Customer & Business Understanding: Ability to translate analytical findings into customer insight and connect to business strategy.
• Experimentation & Analytical Rigor: High-quality experiment design, sound statistical analysis, and clear, actionable readouts.
• Insight Generation & Storytelling: Ability to create compelling narratives that shape product and algorithmic decisions.
• Cross-Functional Collaboration: Strong communication, expectation management, and relationship-building across Product, Engineering, and Data Science.

Pay & Benefits

The annual salary range for this position is $143,000.00 - $286,000.00. Additional compensation includes annual or quarterly performance bonuses and stock. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities, ranging from high school completion to bachelor's degrees, including English Language Learning and short-form certificates, with tuition, books, and fees completely paid for by Walmart.

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