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About This Role
Position Summary...
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What you'll do...
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Role summary:
Walmart is seeking a Principal Data Scientist to lead advanced analytics initiatives that drive strategic business decisions. This role involves developing and deploying machine learning models, performing complex data analysis, and collaborating across functions to translate business challenges into data\-driven solutions. The ideal candidate will apply expertise in statistical modeling, software engineering, and data visualization to deliver impactful insights. Additionally, this position requires mentoring team members, ensuring model robustness, and supporting scalable deployment to enhance Walmart’s data capabilities and operational effectiveness.
About the team:
Sam’s Club Applied AI Labs develops advanced AI solutions that empower merchants and club teams to make faster, data\-driven decisions. The team delivers impactful machine learning and agentic tools across assortment, pricing, and replenishment, transforming data into actionable insights used daily throughout the business. Operating with high ownership, the team manages projects end to end, focusing on real\-world adoption and measurable impact. Members collaborate closely to build scalable AI systems that drive business value, continuously innovating and deploying solutions that enhance operational efficiency and decision\-making across the organization.
What you'll do:
- Architect and scale agentic AI copilots that help merchants and business teams make faster, sharper decisions.
- Design and ship LLM and agentic systems — tool\-calling, retrieval, multi\-step reasoning — from prototype to production.
- Build rigorous evaluation, guardrails, and observability so AI solutions stay accurate, safe, and trusted at scale.
- Turn complex business workflows and large datasets into reliable, high\-impact AI capabilities.
- Partner with product, engineering, and business stakeholders to translate real problems into technical solutions.
- Set technical direction and mentor data scientists on agentic AI, modeling, and engineering best practices.
What you'll bring:
- Deep experience building and deploying machine learning and LLM/agentic systems in production.
- Strong Python and SQL, with solid software engineering and MLOps/LLMOps skills.
- Hands\-on expertise with agentic frameworks, tool\-calling, retrieval\-augmented generation, and prompt and evaluation design.
- Proven ability to design evaluation, guardrails, and observability for generative AI.
- Skill translating ambiguous business needs into scalable, well\-architected AI solutions.
- A track record of technical leadership — setting direction, raising the bar, and mentoring teams.
- A bias for impact: you measure success by real adoption and business outcomes, not demos.
At Sam's Club, we offer competitive pay as well as performance\-based bonus awards and other great benefits for a happier mind, body, and wallet!
\-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, parental leave, family care leave, bereavement, jury duty, and voting. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable.
For information about PTO, see https://one.walmart.com/notices.
\- 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 company paid education benefit program for full\-time and part\-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short\-form certificates. Tuition, books, and fees are completely paid for by Walmart.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
The annual salary range for this position is $110,000\.00 \- $220,000\.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include Regional Pay Zone (RPZ) (based on location).
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Minimum Qualifications...
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*Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.*
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related fieldPreferred Qualifications...
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*Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.*
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2\.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.Primary Location...
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2101 Se Simple Savings Dr, Bentonville, AR 72712\-4304, United States of America
Walmart and its subsidiaries are committed to maintaining a drug\-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.
Salary Context
This $110K-$220K range is above the median for Data Scientist roles in our dataset (median: $160K across 258 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Sam's Club, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 789 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($165K) sits 14% below the category median. Disclosed range: $110K to $220K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Sam's Club AI Hiring
Sam's Club has 2 open AI roles right now. They're hiring across Data Scientist. Based in Bentonville, AR, US. Compensation range: $220K - $220K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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