Staff, Data Scientist

What you'll do at

Position Summary...

What you'll do...

The Reliability Engineering group at Walmart Global Tech builds data-driven platforms that ensure the availability, performance, and efficiency of Walmart’s enterprise and e-commerce systems at scale. The team leverages large-scale telemetry, advanced analytics, and automation to drive intelligent decision-making across infrastructure and applications. By owning core capabilities such as continuous profiling, distributed tracing, and policy-driven runtime management, the group enables proactive optimization, faster detection of issues, and resilient system behavior across thousands of services.

About Team:
Building the right technology foundation for Infrastructure & platforms is vital to success at the scale of Walmart. Our team builds and maintains the foundational technologies that support the tech organization. Included in this are data platforms, enterprise architecture, DevOps, cloud computing, and infrastructure. All of these products and services are supported by scalable and powerful infrastructure, ensuring a secure and seamless employee and customer experience across stores, digital channels, and distribution centers.

What you'll do:

As a Staff Data Scientist within Walmart Global Tech organization, you will lead the design and deployment of production-grade ML systems that improve the reliability, scalability, and efficiency of our enterprise and e-commerce platforms. You will work hands-on across the full lifecycle—analyzing large-scale telemetry, building and shipping models, and writing high-quality code that integrates directly into runtime systems. Your solutions will power smart autoscaling, anomaly detection, seasonality-aware forecasting, and capacity optimization across thousands of services, enabling real-time, autonomous decision-making. This is a high-impact role where models run in production, influence system behavior at scale, and where you shape technical direction and best practices for applying ML to large distributed systems.

What you'll bring:

Core Experience

• 5+ years of experience in data science or applied machine learning.

• 5+ years deploying ML models in production.

• Proven track record of owning systems end to end in high-availability environments.

Technical Skills (Hands-On)

• Expert-level Python (NumPy, Pandas, SciPy, Scikit-learn).

• Practical understanding of Kubernetes autoscaling

• Experience working with metrics, logs, and traces from distributed systems.

• Comfortable querying and analyzing large datasets using SQL and time-series databases.

Systems & Cloud Understanding

• Strong understanding of distributed systems behavior (latency, load, failures, cascading effects).

• Hands-on exposure to Kubernetes, cloud platforms and production observability stacks.

• Ability to reason about trade-offs between accuracy, latency, reliability, and safety in ML-driven automation.

Nice to Have

• Agentic systems with evaluation strategies.

• Experience building predictive or adaptive autoscaling systems.

• Knowledge of reinforcement learning or control systems for resource optimization.

• Experience with AIOps, incident prediction, or self-healing platforms.

• Familiarity with streaming ML or online learning approaches.

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.

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Minimum Qualifications...

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 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.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, 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...

1345 Crossman Ave, Sunnyvale, CA 94089-1114, 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.