Staff, Data Scientist - Spark Driver Platform | Sunnyvale

Position Summary

Walmart is actively hiring a Full Stack Staff Data Scientist skilled in building and scaling models, with a strong statistical background, expertise in reinforcement learning, deep learning, personalization, and optimization. Join us to shape the future of retail by leveraging advanced analytics to deliver personalized and optimized experiences for our customers.

About Role

This is a key role as a Tech Lead and contributor to Machine Learning efforts across several key domains in Walmart Spark Driver Platform. You will leverage advanced machine learning and optimization methods to tackle real-world problems, such as driver-trip matching, driver offer pricing, surge pricing, supply/demand forecast, ETA prediction, and Generative AI personalization. The ML models in these domains vary from forecasting models to deep learning models, causal ML models, reinforcement learning models, and recommendation systems. You will play a critical role in driving innovation and optimizing revenue through the application of advanced statistical and machine learning techniques.

What You'll Do

• Build scalable production systems that can handle the training and predictions of ML models for Walmart's Last mile business use cases.
• Build data pipelines from multiple sources and extract data insights using data exploration and visualization techniques.
• Design, implement, productionize, and deploy data science products with consideration of optimality and computational complexity.
• Collaborate with stakeholders, including product, backend engineering, and business operations teams to ensure data science products support Walmart's business objectives.
• Explore the latest trends in machine learning, reinforcement learning, and GenAI techniques to solve complex data challenges.
• Provide mentorship to junior team members.

What You'll Bring

• Ph.D. or equivalent advanced degree in Computer Science, Statistics, Operations Research, Economics, Mathematics, or other quantitative fields with 5+ years of relevant work experience.
• Solid knowledge in advanced forecasting, deep learning, reinforcement learning, and scalable ML architecture.
• Preferred experience in personalization, ranking, causal inference, and GenAI.
• Extensive ML engineering experience deploying and monitoring large-scale machine learning models in production environments.
• Experience implementing and managing ML Ops practices to streamline the machine learning development lifecycle.
• Demonstrated ability to drive projects from conception to completion in a fast-paced, dynamic environment.
• Excellent communication and leadership skills with the ability to influence and inspire cross-functional teams.

About 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, and service professionals within the world's leading retailer who make an epic impact and are at the forefront of the next retail disruption. We are people-led and tech-empowered.

Flexible, Hybrid Work

We use a hybrid way of working that is primarily in office coupled with virtual when not onsite. Our campuses serve as a hub to enhance collaboration.

Benefits

Beyond competitive pay, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and more.

Equal Opportunity Employer

Walmart, Inc. is an Equal Opportunity Employer - By Choice.

Minimum Qualifications

Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Master's 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.