(IND) SENIOR, DATA SCIENTIST

Position Summary...

Walmart is a multi-national, people-led, tech-powered omnichannel retailer with over 2.2M associates.

Associate AI Experience team within the AI & Data pillar is dedicated to empowering field associates, business users, and developers alike with seamless, governed AI embedded into everyday workflows to elevate productivity.

We build a unified, personalized, and trusted super-agent ecosystem that transforms how work gets done.

By putting intuitive agent creation tools directly into the hands of associates, our organization enables domain experts across the enterprise to seamlessly build, test, evaluate, and deploy their own grounded AI agents—connecting their team's knowledge, automating complex tasks, and driving productivity with built-in governance.

Our team is looking for a Senior Data Scientist to own end-to-end design, development, and operation of production GenAI, agentic AI, and ML systems that accelerate the journey from idea to AI-powered solution across the enterprise.

You will architect stateful, reliable, and cost-aware AI experiences on top of our foundational data platforms and ML infrastructure, drive evaluation and trustworthy AI practices, partner closely with product, engineering, and platform teams, and mentor junior data scientists — directly shaping the AI productization and Associates builder solutions that empower millions of Walmart associates and data practitioners.

As part of Walmart Global Tech in India building solutions across global Walmart markets, your designs and AI solutions will have a direct, daily impact on millions of associates.

You will be challenged with complex business and technical problems that span multiple countries, massive data scale, and enterprise-wide adoption.

What you'll do...

Walmart is a multi-national, people-led, tech-powered omnichannel retailer with over 2.2M associates.

Associate AI Experience Org is dedicated to empowering field associates, business users, and developers alike with seamless, governed AI embedded into everyday workflows to elevate productivity.

We build a unified, personalized, and trusted super-agent ecosystem that transforms how work gets done.

By putting intuitive agent creation tools directly into the hands of associates, our organization enables domain experts across the enterprise to seamlessly build, test, evaluate, and deploy their own grounded AI agents—connecting their team's knowledge, automating complex tasks, and driving productivity with built-in governance.

What you'll do: Translate and co-own business problems within the data science discipline into data-driven or mathematical solutions; identify appropriate methods and tools, and demonstrate through use cases how each approach addresses the business need Own end-to-end design, development, deployment, and operation of production AI/ML and GenAI systems, including agentic AI workflows using LangChain, LangGraph, or equivalents — enabling multi-step reasoning, tool use, planning, and autonomous task execution Architect and operate stateful AI systems — conversation state, long-term memory, context persistence, and retrieval strategies — to support reliable, personalized, multi-turn experiences Drive evaluation strategy for GenAI and ML systems, including offline benchmarks, online A/B experimentation, and continuous quality monitoring Uphold and advance trustworthy AI practices: guardrails, human-in-the-loop, monitoring, governance, and safety mechanisms for agent-based systems Identify and propose high-value AI/ML and agentic AI use cases; rapidly build MVPs and POCs to validate feasibility, performance, and impact Select the most suitable analytical modeling techniques for structured, complex data and develop custom models; conduct EDA (statistical analysis, hypothesis testing, inference); design and run experiments; introduce new or revised features based on model responses; mentor junior associates on basic modeling and analytics techniques Identify model evaluation metrics and apply best-practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and ensembles Support deployment of analytical models into production at the required scale; contribute to evaluation, monitoring, and long-term sustainability of deployed models Write production-quality code using the recommended programming languages and approved testing approach to deliver solution and application features driven by business, technical, and data requirements Drive technical design discussions, write design documents and RFCs, and influence team-wide engineering and ML practices Participate actively in the hiring process — conducting technical interviews, raising the bar, and advocating for diverse talent Mentor junior data scientists and contribute to design and code reviews to raise the technical bar across the team What you'll bring: 6+ years of professional experience designing, developing, deploying, and maintaining scalable, production-grade AI/ML and GenAI systems Bachelor's or Master's degree in computer science, engineering, statistics, mathematics, economics, or a related quantitative field Strong industry experience building production AI/ML systems, preferably at large technology companies or AI-native startups Hands-on experience designing and deploying GenAI solutions in production, including Retrieval-Augmented Generation (RAG), advanced prompt engineering, and orchestration patterns Working familiarity with agentic AI patterns and frameworks such as LangChain, LangGraph, or equivalent for tool-use, workflow orchestration, and multi-step reasoning Experience managing conversational context, memory, and state — including retrieval strategies, session management, and personalization techniques Experience driving LLM/GenAI evaluation strategy: offline benchmarks, online A/B experimentation, red-teaming, guardrails, and continuous quality monitoring Deep foundational knowledge of statisti