(USA) Senior, Data Scientist

Position Summary...

What you'll do...

About Walmart Walmart employs more than 2.3 million associates worldwide, with 1.6 million associates in the U.S. Each year, Walmart hires 500,000 applicants to fill thousands of job profiles from engineers, designers, and marketers to pilots and buyers. We promote over 300,000 people annually to positions of greater responsibility. About People Technology Team The Enterprise People Technology team supports the successful deployment and adoption of new People technology across the enterprise. As a Fortune #1 company, our work impacts millions of associates globally. We strive to continuously improve people technology and products to help managers and associates focus on what matters most - supporting our customers and members. People Technology is a significant segment of Walmart Global Tech’s Enterprise Business Services, invested in building a compact, robust organization that includes service operations and technology solutions for Finance, People, and the Associate Digital Experience. About People.AI Team The People.AI team is responsible for developing and deploying AI/ML solutions supporting the Walmart associates globally. In this role, you will build an LLM-powered intelligent experience within a chatbot or business application to enhance associate experience and productivity. You will design and build an intelligent conversational interface that improves communication, automates tasks, accesses data and insights, and provides personalized Q&A support to associates, ultimately creating a more efficient and engaging work environment. What You'll Do Develop LLM-powered intelligent experiences that interpret and generate insights from both tabular and unstructured data. Build and optimize personalized Q&A systems using large language models, enabling context-aware responses tailored to user needs. Design and enhance conversational talent recommendation systems, combining autonomous agent architectures with personalized recommendation algorithms. Advance traditional recommendation systems by evolving them from simple ranked lists to multi-topic, interactive experiences that better reflect user intent. Construct multi-agent intelligent workflows that translate natural language inputs into complex, goal-directed task sequences. Collaborate within a highly cross-functional team, including data scientists, machine learning engineers, product managers, and UX designers. Partner with fellow data scientists to design, prototype, and iterate on AI/ML models and system architectures. Work closely with machine learning engineers to deploy, monitor, and optimize scalable AI/ML solutions in production environments. Collaborate with product managers to design intuitive user experiences, define feedback loops, and analyze user telemetry to guide product improvements. Engage in end-to-end AI/ML product development, from ideation to deployment, while continually expanding your technical and product skillset. Follow and help define robust development standards to ensure the creation of trustworthy, safe, and responsible AI systems. Contribute to internal and external AI/ML research through experimentation, whitepapers, and collaboration with the broader AI community. What You'll Bring Proven experience deploying high-risk NLP applications in real-world, production environments—such as those involving regulatory compliance, privacy, safety, or fairness. Demonstrated ability to advance and implement Trustworthy AI and Responsible ML practices, working cross-functionally with engineering, legal, policy, and product stakeholders across a large enterprise. Track record of mentoring and coaching junior data scientists, especially in navigating ambiguous or novel problem spaces. Strong applied machine learning experience, with solid foundational knowledge in statistics, optimization, and deep learning—preferably gained at leading technology companies (e.g., Google, Meta, Microsoft) or AI-first startups. Excellent communication skills with the ability to synthesize complex technical work into accessible insights for executive briefings, research publications, and external presentations. Advanced proficiency in Python and common ML/DS libraries such as NumPy, pandas, scikit-learn, as well as deep learning frameworks like TensorFlow, PyTorch. Experience designing and deploying scalable deep learning systems, including neural network architecture optimization, model distillation, quantization