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About This Role
Position Summary...
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What you'll do...
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The Principal Data Scientist in the Data Science team will play a crucial role as an architect, leading AI explorations, research, algorithmic solution creation, and fast prototyping aimed to deliver impactful initiatives within the Sam's Club division of Walmart Inc. The position involves developing the foundational ML/AI models that will drive a tailored and enjoyable member experience across our eCommerce, Scan \& Go, and in\-club shopping interactions. As the Principal Data Scientist, you will oversee end\-to\-end implementation of Machine Learning products in the domains of Search and Ads. You will guide a scrum team and collaborate with an accomplished team of Product Managers and Technologists to implement ML/AI solutions at scale. This offers a thrilling chance to integrate retail industry knowledge with machine learning algorithms, upsetting traditional business practices to achieve ambitious growth objectives. In this capacity, you will join a vibrant group of high\-achieving individuals spanning Search, Personalization, and Conversational AI, leading impactful and transformative shifts in our business. The position is based in Dallas, Texas, and you will be reporting to the Architect of Search and Ads.
What you'll do: You’ll sweep us off our feet if…
- You have experience in the development of large\-scale production systems, Knowledge of Search, information retrieval and ranking systems.
- You have experience building large scale ML systems in public cloud like Azure, Google etc
- 3 years\+ of experience in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Deep Neural Networks, Wide and Deep etc
- You are skilled in Programming language (Python, Java, R or Scala) and Large\-scale training using data structures and algorithms
- Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit\-Learn, or Spark MLLib
- You have experience with cloud environments such as Azure, Google Cloud, etc.
- Solid MLOps practices including good design documentation, unit testing, integration testing and source code control (git).
- You are experienced with agile methodologies using project planning and tracking management tools e.g., JIRA
- You’re naturally curious on how things work and excited by solving challenges at the scale of a Fortune 1 Retailer.
You’ll make an impact by…
- Leading a team of Data Scientists and Engineers focused on backend software infrastructure for powering AI/ML solutions
- Partner closely with Product and engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.
- Executing full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross\-functional partners.
- Building MLOps framework to create, build and deploy data science algorithms continuously test and personalize user experience
- Leading a team of Data Scientists and Engineers focused on backend software infrastructure for powering AI/ML solutions
- Partner closely with Product and engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.
- Executing full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross\-functional partners.
- Building MLOps framework to create, build and deploy data science algorithms continuously test and personalize user experience
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.
Sunnyvale, California US\-11807: The annual salary range for this position is $143,000\.00 \- $286,000\.00
Bentonville, Arkansas US\-10735: 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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815 Eleventh Ave, Sunnyvale, CA 94089\-4731, 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 $143K-$286K range is above the 75th percentile for Data Scientist roles in our dataset (median: $166K across 345 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 26,159 AI roles we're tracking, Data Scientist positions make up 2% 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 $204,700 based on 441 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($214K) sits 5% above the category median. Disclosed range: $143K to $286K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Sam's Club AI Hiring
Sam's Club has 8 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Groveport, OH, US, Lithia Springs, GA, US, Bentonville, AR, US. Compensation range: $98K - $286K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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