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Position Summary... What you'll do...About the Role We’re looking for a Staff Data Scientist to design and build advanced forecasting models to ensure accurate financial planning and analysis (FP&A) that power critical business decisions. You’ll build and deploy state-of-the-art time series models (classical + ML + deep learning), drive explainability and trust (XAI), and explore next-generation approaches such as graph neural networks for spatiotemporal and relational forecasting problems. You’ll partner closely with engineering, product, and stakeholders to deliver measurable impact at scale. What You’ll Do

• Design and deploy statistically and ML models to address high-impact financial forecasting needs, ensuring alignment with Walmart’s business objectives.
• Perform statistical analysis across large data sets and within defined segments to empower data driven decisions.
• Own E2E forecasting lifecycle, including scoping, feature engineering, model development, experimentation, monitoring and ongoing performance optimizations.
• Develop advanced time series solutions using:
  • Statistical methods (ETS, ARIMA/SARIMA, State Space Models)
  • ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features)
  • Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM)
  • Probabilistic forecasting and uncertainty quantification (quantile regression, Bayesian approaches, conformal prediction, prediction intervals)
• Build explainable forecasting systems: model interpretability, feature attribution, drivers of change, scenario analysis, and stakeholder-facing narratives.
• Apply graph-based and spatiotemporal modeling where relationships matter: GNNs, temporal graphs, graph embeddings.
• Establish strong evaluation and monitoring: backtesting, leakage prevention, stability checks, drift detection, calibration of uncertainty, and post-deployment performance tracking.
• Drive best practices in MLOps and production readiness: reproducible pipelines, scalable training/inference, model versioning, and governance.
• Build Agentic workflows to enable chat based forecasting explainability and scenario planning.
• Collaborate with cross-functional partners including Product, Business, Data Science and Engineering.
• Mentor other data scientists, set modeling standards, and influence technical direction across teams.

What You’ll Bring (Required)

• 8+ years in data science / applied ML (or PhD + 5 years), with deep hands-on exposure to forecasting and predictive modeling.
• Demonstrated experience delivering production grade ML models with measurable business outcomes.
• Strong knowledge of time series topics: seasonality, hierarchies, intermittent demand, holidays/events, promotions, missingness, outliers, anomaly detection, and regime changes.
• Hands-on experience with deep learning frameworks (PyTorch or TensorFlow) and modern architectures for time series.
• Practical experience with explainable AI methods and communicating model reasoning to non-technical stakeholders.
• Excellent coding skills in Python; strong grasp of software engineering fundamentals (testing, packaging, code reviews).
• Ability to translate ambiguous business problems into rigorous modeling plans and deliver results.
• High attention to detail and an ownership mindset in managing multiple high-impact projects.

Preferred Qualifications

• Experience with graph neural networks (PyG/DGL), spatiotemporal GNNs, or temporal graph learning.
• Experience with causal inference or decision-focused forecasting (uplift, impact estimation, counterfactuals, policy evaluation).
• Familiarity with large-scale data/compute: Spark, distributed training, feature stores, GPU workflows.
• Experience building human-centered explainability: dashboards, driver decomposition, “why changed” analysis, model cards.
• Publications, patents, or open-source contributions in time series, XAI, or graph learning.

Key Skills / Tech Stack

• Proficiency in Python, Sql and data visualization tools.
• Experience using PyTorch/TensorFlow; scikit-learn; XGBoost/LightGBM and other models for production grade models.
• Experience building solutions with time series libraries (statsmodels, Prophet-like tools, etc.)
• Interest and exposure to explainability: SHAP, Integrated Gradients, permutation importance, counterfactuals.
• Nice to have:
  • Experience with data platforms like Spark/Databricks, Airflow, Kubernetes
  • MLOps/AgentOps experience in deployment model and/or Agentic workflows at scale.

At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
The annual salary range for this position is $143,000.00 - $286,000.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock

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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... 809 11th Ave, Sunnyvale, CA 94089-4731, 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.