Staff, Data Scientist

Walmart•Bentonville, AR

1d•$110,000 - $220,000

About The Position

Walmart’s Decision Management Team supports the growth of the e-Commerce Marketplace program through the practical application of data science and advanced analytics to optimize risk decision strategies. This includes large-scale data analysis, advanced statistical modeling, case investigation, and production-grade machine learning systems to manage risk on the ecommerce platform. We partner closely with business, product, engineering, and operations teams to design and deploy scalable, intelligent risk solutions that protect the Marketplace ecosystem. What You’ll Do As a Staff Data Scientist, you will operate as a technical leader and strategic driver within the organization. You will define long-term modeling strategy, architect scalable risk detection systems, and lead complex, high-impact initiatives that shape Marketplace risk management. This role requires deep technical expertise, strong business acumen, and the ability to influence across organizational boundaries. You will elevate the quality and impact of data science across the team by setting technical standards, mentoring senior scientists, and driving innovation in AI-powered risk systems.

Requirements

Deep expertise in machine learning, statistical modeling, anomaly detection, and their application to large-scale fraud and risk detection systems.
Proven experience architecting and deploying production-grade ML systems in real-time or near-real-time environments.
Strong systems-thinking mindset with experience designing model pipelines, feature stores, monitoring systems, and feedback mechanisms.
Advanced proficiency in Python, SQL, and modern ML frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
Experience leading technically complex, ambiguous initiatives with measurable business impact.
Strong understanding of Agentic AI systems, autonomous workflows, and AI-driven decision architectures.
Experience applying GenAI techniques for data augmentation, model robustness, or simulation-based learning.
Expertise in experimentation methodologies including A/B testing, causal inference, uplift modeling, and statistical validation.
Demonstrated ability to influence technical direction and drive alignment across product, engineering, and leadership teams.
Excellent communication skills with the ability to operate at both executive and deeply technical levels.
Option 1: Bachelor’s degree in Statistics, Computer Science, Data Science, Mathematics, or related field with 8+ years of experience in data science, machine learning, or applied risk management.
Option 2: Master’s degree in a related field with 6+ years of applied experience in machine learning or large-scale risk analytics.
Option 3: 10+ years of direct experience in data science, machine learning, or fraud/risk management within e-commerce, fintech, or marketplace ecosystems.

Nice To Haves

Expertise in advanced ML methods such as deep learning, graph modeling, reinforcement learning, or advanced anomaly detection.
Experience with LLMs, agentic workflows, prompt engineering, and AI-augmented decision systems in production settings.
Strong background in distributed computing and big data technologies (e.g., Apache Spark, Hadoop) and cloud-native ML systems (AWS, Google Cloud).
Experience designing model governance frameworks including fairness, explainability, and compliance standards.
Proven record of technical leadership, mentorship, and cross-team influence at scale.
Experience building and optimizing feature engineering pipelines and model evaluation frameworks (ROC/AUC, precision/recall, F1, calibration, drift detection).
Track record of delivering measurable impact in high-scale, high-ambiguity environments.
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.

Responsibilities

Define Risk Modeling Strategy by setting the long-term vision for fraud detection, anomaly detection, and performance risk mitigation across the Marketplace.
Architect Scalable Risk Systems that integrate machine learning models, real-time decision engines, and feedback loops into robust production environments.
Lead Development of Advanced Risk Models using supervised, unsupervised, deep learning, and reinforcement learning techniques to proactively detect emerging fraud patterns.
Drive Innovation in Agentic AI Frameworks to build adaptive, semi-autonomous decision systems capable of evolving with dynamic fraud behaviors.
Champion Generative AI Applications such as synthetic data generation, adversarial simulations, and scenario modeling to strengthen model resilience and stress testing.
Own End-to-End Model Lifecycle Governance, including experimentation design, validation frameworks, monitoring infrastructure, drift detection, and retraining strategies.
Translate Business Strategy into Technical Roadmaps by aligning risk modeling priorities with company-level objectives and measurable impact metrics.
Lead Deep-Dive Strategic Analytics that influence risk policies, operational design, and product strategy at the organizational level.
Establish Best Practices in experimentation, statistical rigor, explainability, fairness, and responsible AI deployment.
Mentor and Uplevel Data Scientists, providing technical guidance, code reviews, design feedback, and thought leadership.
Influence Cross-Functional Stakeholders by clearly communicating complex methodologies and trade-offs to executive and non-technical audiences.
Drive Enterprise-Level Experimentation including multi-variant testing, causal inference studies, and large-scale impact evaluations.

Benefits

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 $110,000.00 - $220,000.00
Additional compensation includes annual or quarterly performance bonuses.
Additional compensation for certain positions may also include : - Stock