Data Scientist III in Sunnyvale, California

Data Scientist

Bentonville, AR: $90,000 - $180,000/yr Sunnyvale, CA: $117,000 - $234,000/yr Regular/ Permanent Salaried

Position Summary:

As a Data Scientist at Walmart, you will leverage advanced analytical techniques and domain expertise to identify, develop, and deploy data-driven solutions that support strategic business objectives. This role requires proficiency in data sourcing, model development, validation, and scalable deployment, alongside strong coding and visualization skills. You will collaborate across functions to translate complex business challenges into actionable insights, mentor team members, and ensure alignment with data governance and quality standards.

Your contributions will drive informed decision-making and enhance operational efficiency within a dynamic, data-centric environment.

About the team:
Our team partners closely with Walmart U.S. stores and eCommerce to enhance customer experiences through technological innovation. We leverage data science and advanced analytics across categories such as groceries, entertainment, and sporting goods. Focus areas include in-store service, merchant tools, search, and personalization. By integrating data-driven insights and scalable solutions, the team supports business growth and operational excellence. This collaborative environment empowers team members, stores, and merchants to deliver seamless shopping experiences both online and in-store, driving continuous improvement and value creation.

What you'll do:

• Develop scalable time series forecasting systems leveraging global models like Temporal Fusion Transformers, N-BEATS, and PATCHTST, enabling robust forecasting across thousands of retail and e-commerce time series.
• Foundational Knowledge on advanced regression.
• Apply generative AI to synthesize time series data, enhance model training pipelines, and build intelligent NLP-based assistants for analytics enablement.
• Design and train large-scale neural networks for time series, anomaly detection, and causal inference, with deployment via automated batch pipelines
• Build and maintain production-ready applications on cloud platforms, integrated with internal systems to deliver insights at scale.
• Collaborate with cross-functional teams to define objectives, formulate hypotheses, and deploy models that directly influence decision-making.

What you'll bring:

• Strong foundation in time series forecasting, deep learning, and optimization theory, with a focus on sequence modeling and attention-based architectures.
• Experience in training and deploying transformer-based neural networks (e.g., TFT, LSTM, GPT variants) for real-world business applications.
• Proficient in Python, SQL, and hands-on with PyTorch, Tensor Flow/Keras, Scikit-learn, and stats models.
• Demonstrated ability to work on GPU-based model training pipelines, and exposure to managing experimentation at scale.