Principal Data Scientist, Experimentation Sciences

Walmart

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Sunnyvale, CABentonville, AR
Salary: $143,000–$286,000 / yr
Employment: Full-time
Posted: 172 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $192k

This role $214k

$126k $303k

below market most similar roles pay here above market

This role pays more than 70% of similar roles. Most pay $165,000–$218,875 — the blue band above. At the midpoint, this role pays about $214k versus about $192k for comparable roles.

Based on 240 similar postings.

Employer

About Walmart

Walmart Inc. is the world''s largest retailer by revenue, operating a chain of hypermarkets, discount department stores, and grocery stores, as well as a growing e-commerce presence through Walmart.com. Industry: General Merchandise & Grocery Retail

Walmart currently has 724 open roles on FindRole.

Listed pay typically runs $117,000–$234,000 across 593 roles with salary data.

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At a glance

TL;DR · Principal Data Scientist, Experimentation Sciences

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JOB TITLE: Principal, Data Scientist, Experimentation Sciences As a Principal Data Scientist, you will join the team managing the experimentation platform to define and execute the data science roadmap for A/B testing across multiple channels. You will lead the scientific direction for experiment reporting, dashboards, and reusable measurement services, ensuring exposure data links to business outcomes with rigor. Your daily work involves designing scalable statistical frameworks for online experiments, including guardrails, heterogeneity analysis, and sequential decisioning. You will also develop AI-native evaluation strategies for LLM evals and prompt evaluation. To achieve this, you will utilize Python, SQL, PySpark, Airflow, and Google Cloud Platform technologies. You will build robust data models and pipelines to modernize statistical tooling and improve self-service experimentation for complex retail and marketplace operational feedback loops.

What does a Data Scientist earn in California?

Median $214500 from 136 postings across 32 companies.

See salary data

Skills

Python SQL PySpark Spark Google Cloud Platform Airflow Causal Inference A/B Testing scikit learn TensorFlow Scala R ETL Observability

What you'll do

Define and execute the multi-year data science roadmap for the experimentation platform and measurement services.
Lead the design of scalable statistical frameworks for online experiments, including guardrails and variance reduction.
Partner with data engineering to design robust SQL and PySpark data models and pipelines for experimentation data.
Establish and govern canonical experiment metrics, scorecards, and reporting standards across all business channels.
Define the strategy for AI-native experimentation, including LLM evaluation frameworks and prompt evaluation methods.
Build lightweight proofs of concept and automated workflows using Python, SQL, and Airflow to validate new ideas.
Serve as the senior technical advisor to leadership on experimental design, causal interpretation, and measurement risk.

What we're looking for

Must have a Bachelor's degree in a quantitative field and 5 years of experience in an analytics-related field.
Must have a Master's degree in a quantitative field and 3 years of experience in an analytics-related field.
Must have 7 years of experience in an analytics or related field.
Must demonstrate strong hands-on experience with SQL, Spark/PySpark, experimentation, and causal inference at production scale.
Must have deep expertise in experimentation, causal inference, and statistical decision-making to shape organizational experiment design and analysis.
Must have expert-level SQL and PySpark skills and strong Python skills for high-volume, distributed data pipelines.
Must have experience building or materially improving experimentation platforms, measurement systems, or internal science tooling.
Must have working knowledge of modern AI evaluation methods, including LLM evals and prompt experimentation.

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