(IND) PRINCIPAL, DATA SCIENTIST
Walmart
Data Science
Bengaluru, Karnataka, India
Position Summary...
What you'll do...
About Team:
As part of the Walmart Applied AI team and lead the next generation of decision science for Walmart’s supply chain, replenishment, and fulfillment ecosystem. This role sits at the intersection of large-scale optimization, machine learning, simulation, and intelligent operational tooling, with direct impact on how Walmart allocates inventory, reduces waste, improves in-stock performance, and scales complex planning decisions across stores, clubs, distribution centers, and fulfillment networks.
As a Principal Data Scientist, you will define technical strategy, lead high-impact science programs from concept to production, and partner deeply with Product, Engineering, Operations, and business leaders. You will work on problems such as replenishment optimization, allocation and placement engines, inventory exit decisions, demand-splitting logic, shelf-capacity and fit-to-shelf design, and AI-assisted workflow automation. This is a hands-on leadership role for someone who can drive both scientific rigor and business adoption at enterprise scale.
What You’ll Do
- Lead the design and delivery of advanced optimization, machine learning, and decisioning solutions for high-value retail and supply chain problems, including replenishment, placement, inventory flow, and fulfillment planning.
- Shape the technical roadmap for systems such as replenishment override agents, allocation and placement engines, item exit optimization, fit-to-shelf logic, and demand-splitting workflows.
- Build and productionize scalable models and algorithms that operate across large datasets, complex business constraints, and network-level decisions spanning stores, DCs, and fulfillment centers.
- Partner with product managers, engineers, and business stakeholders to define problem statements, success metrics, experimentation approaches, and production roll-out strategies.
- Translate ambiguous operational challenges into mathematically rigorous and implementable solutions, including optimization formulations, heuristics, simulations, predictive models, and decision-support tools.
- Drive architectural decisions for production-grade science systems using modern cloud and distributed data platforms.
- Set a high technical bar through code quality, validation strategies, experimentation discipline, observability, and safe deployment practices.
- Mentor senior and junior data scientists, provide technical guidance across projects, and help scale reusable science patterns, frameworks, and best practices across the team.
- Communicate findings, tradeoffs, and business impact clearly to leaders across science, engineering, and operations.
- Identify innovation opportunities that can translate into patents, reusable platforms, and step-change business outcomes.
What You’ll Bring
- Deep expertise in one or more of the following: operations research, mathematical optimization, machine learning, applied statistics, econometrics, or large-scale decision science.
- A strong track record of solving ambiguous business problems using rigorous science and getting those solutions into production.
- Experience building systems that combine modeling, optimization, business rules, and engineering constraints in real-world operating environments.
- Ability to influence technical strategy across cross-functional partners and align science work to measurable business outcomes.
- Strong coding and software design skills, with the ability to work effectively in production-oriented environments and collaborate closely with engineering teams.
- Comfort working across a broad problem space that may include optimization, forecasting, allocation, recommendation, experimentation, agentic systems, and workflow automation.
- Excellent executive communication, stakeholder management, and mentoring skills.
Minimum Qualifications
- Masters or PhD with > 10 years in Computer Science, Statistics, Mathematics, Operations Research, Economics, Engineering, or related quantitative field and 8+ years of experience in data science, machine learning, optimization, or related field.
- Experience leading complex technical initiatives from problem framing through production deployment and business adoption.
- Experience working with Python and modern data/science tooling in cloud or distributed computing environments.
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 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 field.Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.