Position Summary...
The Staff Data Scientist – International eCommerce Personalization will define and drive the long-term technical strategy, ML architecture, and scientific standards for personalization across Walmart's international digital commerce platforms. You will own the most ambiguous, highest-leverage problems across the personalization stack — from novel model architectures and system-level experimentation frameworks to multi-market adaptability and responsible AI at scale. You will operate as a force multiplier: influencing engineering and product roadmaps, elevating the capabilities of senior and principal data scientists, establishing best practices that set the standard for personalization science across the organization, and representing Walmart's technical thinking to external research and industry communities. You'll partner at the Director and VP level across Data Science, Engineering, Product, Merchandising, and Marketing to align personalization strategy with Walmart's international business goals.
What you'll do...
About the Team The International eCommerce Personalization Data Science team is part of Walmart's International eCommerce organization. We build intelligent ML and AI systems that make every digital shopping journey more relevant — powering personalized recommendations, search and browse ranking, homepage and content ranking, deals and offer targeting, cross-sell and basket-building, and customer lifecycle engagement across multiple international markets. Our stack spans large-scale behavioral data, streaming inference pipelines, online feature stores, candidate generation and ranking models, experimentation platforms, and LLM-powered analysis and automation workflows. We operate at the intersection of data science, product relevance, real-time engineering, and customer experience — deploying solutions that directly improve customer trust, shopping ease, and Walmart's business outcomes.
What You'll Do
- Define and drive personalization technical strategy: Own the multi-year scientific and architectural roadmap for Walmart's international personalization platform — identifying the most impactful investments in model architecture, data infrastructure, experimentation capability, real-time systems, and AI/ML tooling, and making the case for them at the Director and VP level across Data Science, Engineering, and Product.
- Architect next-generation personalization systems: Lead the design of the end-to-end personalization ML architecture — including candidate generation and retrieval, multi-stage ranking, contextual personalization, real-time feature computation, feedback loops, and model governance — ensuring the system is scalable, low-latency, resilient, privacy-compliant, and adaptable across diverse international markets.
- Solve the hardest personalization science problems: Take on the most ambiguous and technically complex challenges across the personalization stack: multi-objective ranking under business constraints, cross-session and cross-channel personalization, cold start at scale, causal inference for long-horizon customer outcomes, transfer learning and market adaptability, and the integration of large language models into production personalization workflows.
- Establish scientific rigor and standards across the discipline: Define and champion the standards for experimentation design, offline evaluation, model validation, incrementality measurement, and responsible ML across the personalization team and adjacent science teams — building shared frameworks, tooling, and review processes that improve quality and velocity organization-wide.
- Drive cross-functional strategy and organizational alignment: Serve as the primary technical voice of personalization science in cross-functional planning with Engineering, Product, Merchandising, Marketing, UX, Legal, and Analytics — translating complex scientific findings, system tradeoffs, and long-horizon research into strategic recommendations that shape product roadmaps, engineering investments, and business priorities.
- Multiply the impact of the science organization: Provide deep technical mentorship to Senior and Principal Data Scientists — conducting architectural reviews, sponsoring technical growth, and co-developing complex models and systems. Identify organizational gaps in methodology, tooling, and talent and drive initiatives to close them. Elevate the overall scientific capability of the personalization discipline.
- Represent Walmart's personalization science externally: Contribute to Walmart's scientific reputation through publications, conference presentations, patent filings, and participation in the broader research community — attracting top talent and establishing Walmart as a thought leader in large-scale personalization and recommendation systems.
What You'll Bring
- Deep personalization and ML systems expertise at scale: 8+ years of hands-on data science or ML research experience with a PhD in a relevant field (Machine Learning, Statistics, Computer Science, Operations Research, or related discipline), or 12+ years of equivalent industry experience without a PhD — with significant depth in ecommerce personalization, recommender systems, search ranking, customer targeting, or real-time decisioning, including a track record of delivering systems that operate at the scale of hundreds of millions of users in production.
- Technical vision and architectural leadership: Demonstrated ability to define and execute multi-year technical roadmaps for complex ML systems — including candidate generation, multi-stage ranking, real-time serving, feature stores, and experimentation infrastructure — with the authority and communication skills to align engineering, product, and business stakeholders on long-horizon technical investments.
- Advanced ML and research depth: Mastery of the full personalization and recommendation system stack — deep learning retrieval and ranking models, two-tower architectures, transformer-based sequence models, graph neural networks, contextual bandits, multi-task learning, uplift modeling, causal inference, and LLM integration — combined with strong intuition for when to apply research innovations versus proven production patterns.
- Experimentation leadership and causal reasoning: Expert-level ability to design, analyze, and interpret complex experimentation programs — including A/B tests, switchback experiments, synthetic controls, difference-in-differences, and long-run customer outcome measurement — and to establish organizational standards for connecting model improvements to sustainable business and customer impact.
- Cross-functional and executive influence: Proven track record of influencing technical and business decisions at the Director and VP level across Data Science, Engineering, Product, and Marketing in a large, matrixed global organization — communicating scientific strategy, tradeoffs, and recommendations with clarity, rigor, and executive-level persuasion.
- Force multiplier and organizational builder: History of elevating the technical capability of senior data scientists and cross-functional teams — through mentorship, architectural review, shared tooling, and the establishment of scientific standards and best practices that outlast individual project contributions.
- Responsible AI and privacy-aware ML: Deep understanding of fairness, privacy, transparency, and governance considerations in large-scale personalization systems — including experience designing ML systems that comply with regulatory requirements across multiple international markets.
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 expert's 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.
Mode of Work
Walmart’s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our Bangalore office for daily work, with the flexibility for associates to manage their personal lives.
Benefits
Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.
Belonging
We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone.
At Walmart, our vision is "everyone included." By fostering a workplace culture where everyone is—and feels—included, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, we’re able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate.
Equal Opportunity Employer
Walmart, Inc., is an Equal Opportunities 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 inclusive of all people.
Minimum Qualifications...
__Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. __
Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field.
Preferred Qualifications...
__Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. __
Primary Location...
Block- 1, Prestige Tech Pacific Park, Sy No. 38/1, Outer Ring Rd Kadubeesanahalli , India