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About This Role
Position Summary...
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What you'll do...
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*Immigration sponsorship is not available for this role. Applicants must be authorized to work for any employer in the United States without current or future visa sponsorship.*
*This is a full\-time onsite role based in Bentonville, AR or Sunnyvale, CA; remote and hybrid options are not available.* About the Role:
Walmart Global Tech is seeking a talented and experienced Principal Data Scientist specializing in Pricing Algorithms to lead our efforts in developing sophisticated pricing models and strategies. As a Principal Data Scientist, you will play a critical role in driving innovation and optimizing revenue through the application of advanced statistical and machine learning techniques. You will lead a team of data scientists and collaborate closely with cross\-functional teams to develop and implement pricing algorithms that maximize profitability and drive business growth. About the Team: The Applied AI team researches and develops advanced algorithms that power strategic decision\-making across pricing, markdown optimization, price recommendations, price elasticity, assortment optimization, supply chain, replenishment, and store layout. You will work closely with data scientists, machine learning engineers, operations research scientists, and data analysts, while collaborating with business leaders, product managers, pricing strategists, software engineers, and data engineers to build AI\-driven solutions at enterprise scale.
Our work combines techniques from forecasting, optimization, operations research, machine learning (classical ML, deep learning, reinforcement learning), causal inference, experimentation, and statistics to solve complex pricing and retail challenges. We develop innovative AI solutions that directly influence business strategy and customer experience, and our research is regularly published in top\-tier conferences and journals. What You'll Do:
- Strategic Leadership: Provide strategic leadership and technical expertise in the development and implementation of pricing algorithms and models. Define the vision, roadmap, and priorities for pricing optimization initiatives.
- Algorithm Development: Lead the design, development, and deployment of advanced pricing algorithms using state\-of\-the\-art machine learning techniques, including but not limited to regression analysis, demand forecasting, dynamic pricing, and reinforcement learning.
- Code Review: Conduct thorough code reviews of pricing algorithms and related software components developed by the team. Ensure adherence to best practices, coding standards, and optimization techniques. Provide constructive feedback and mentorship to team members to enhance code quality and maintainability.
- Data Analysis and Insights: Utilize large datasets to conduct in\-depth analysis of customer behavior, market dynamics, and competitive pricing strategies. Extract actionable insights to inform pricing decisions and strategy formulation.
- Model Evaluation and Optimization: Oversee the evaluation, validation, and optimization of pricing models to ensure accuracy, reliability, and performance. Implement rigorous testing methodologies to assess model effectiveness and robustness.
- Collaboration and Stakeholder Engagement: Collaborate closely with cross\-functional teams including product management, engineering, marketing, and finance to understand business objectives, requirements, and constraints. Work collaboratively to translate business needs into data\-driven pricing solutions.
- Thought Leadership: Stay abreast of industry trends, best practices, and emerging technologies in pricing analytics, data science, and machine learning. Provide thought leadership and guidance on pricing strategy, methodologies, and implementation best practices.
- Documentation and Communication: Document methodologies, findings, and recommendations in clear and concise manner. Communicate complex technical concepts and insights to non\-technical stakeholders through presentations, reports, and dashboards.
- Mentorship and Knowledge Sharing: Mentor junior team members and provide guidance on technical and methodological aspects of pricing analytics and data science. Foster a culture of learning and knowledge sharing within the team.
What You'll Bring:
- Ph.D. or equivalent advanced degree in Computer Science, Statistics, Mathematics, Economics, or related field.
- Extensive experience (8\+ years) in data science, machine learning, and statistical analysis, with a focus on pricing optimization.
- Proven track record of building and deploying pricing algorithms/models in a real\-world setting.
- Expertise in programming languages such as Python, R, or Scala for data analysis and model development.
- Strong understanding of pricing concepts, methodologies, and strategies in diverse industries.
- Deep knowledge of machine learning algorithms and techniques, with hands\-on experience in applying them to pricing problems.
- Excellent communication and leadership skills with the ability to influence and inspire cross\-functional teams.
- Demonstrated ability to drive projects from conception to completion in a fast\-paced, dynamic environment.
About Walmart Global Tech: Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That's what we do at Walmart Global Tech. We're a team of software engineers, data scientists, cybersecurity experts and service professionals within the world's leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people\-led and tech\-empowered. We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.
Walmart’s culture is a competitive advantage, and it’s fostered by being together. Working together in person allows us to collaborate, align quickly and innovate with greater speed. We use our campuses to create purposeful connections rooted in deepening understanding and investing in the development of our associates.
Benefits:
Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much more.
Equal Opportunity Employer:
Walmart, Inc. is an Equal Opportunity Employer \- by choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing unique styles, experiences, identities, ideas and opinions while being welcoming of all people.
*The above information has been designed toindicatethe general nature and level of work performed in the role. It is not designed tocontainor be interpreted as a comprehensive inventory of all responsibilities and qualificationsrequired ofemployees assigned to this job. The full Job Description can be made available as part of the hiring process**.*
\#LI\-onsite
At Walmart, 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 (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. 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. Live Better U is a Walmart\-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.
Bentonville, Arkansas US\-09104: The annual salary range for this position is $110,000\.00 \- $220,000\.00
Sunnyvale, California US\-11656: The annual salary range for this position is $143,000\.00 \- $286,000\.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock
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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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2608 Se J St, Bentonville, AR 72712, 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-$286K range is above the 75th percentile 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 Walmart, 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. Disclosed range: $110K to $286K.
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.
Walmart AI Hiring
Walmart has 13 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer, AI Software Engineer. Positions span Sunnyvale, CA, US, Bentonville, AR, US. Compensation range: $220K - $481K.
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.
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