Staff, Data Scientist

Walmart, Inc.

$110K — $220K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in building and deploying ML systems at scale
  • Proficiency in data manipulation languages (e.g., Python, SQL)
  • Experience with distributed computing and big data tools (PySpark/GCP/BigQuery)
  • Hands-on experience with Graph Neural Networks (GNNs) and graph processing
  • Familiarity with Generative AI techniques for workflow automation and explainability
  • Desirable: experience in fraud risk solutions
  • Collaboration experience with cross-functional teams in product and engineering

Responsibilities

  • Develop ML models for various fraud detection scenarios in E-Commerce and payment platforms
  • Design graph-based systems for detecting coordinated fraud and risk signals
  • Leverage Generative AI for enhancing detection and automating workflows
  • Collaborate with stakeholders to translate fraud problems into data science initiatives
  • Build scalable ML models using big data mining techniques
  • Implement model pipelines in collaboration with engineering teams
  • Conduct root cause analysis to swiftly address system issues

Benefits

  • Flexible work environment opportunities
  • Access to advanced technologies and tools
  • Collaborative team culture with a focus on innovation
  • Opportunities for career growth and development
  • Support for inclusive digital experience initiatives
Full Job Description
Position Summary...
We are looking for a Staff Data Scientist to join Sam's Club fraud detection team. As a Staff Data Scientist, you will be responsible for owning fraud risks in various product segments and being a strategic partner to product & business teams. You will be tasked to set goals, create strategy, and closely collaborate with product managers, engineers and business stakeholders. You'll be responsible for detecting changed fraud trends, building and implementing ML models with high-dimensional, fast moving real time dataset and driving innovation in detecting & preventing fraud across various channels. You will also help shape the next generation of fraud intelligence by leveraging Graph Neural Networks (GNNs), network-based modeling, and Generative AI (GenAI) techniques to enhance detection accuracy, accelerate investigations, and improve model explainability and decision intelligence.

What you'll do...
  • Use machine learning to develop models for fraud detection in areas such as E-Commerce & In-club payment fraud, Return abuse, Account takeover (ATO) etc.
  • Design and implement graph-based fraud detection systems, including link analysis, entity resolution, and Graph Neural Network (GNN) models to detect coordinated fraud rings and network-level risk signals.
  • Leverage Generative AI techniques (e.g., LLMs and Agentic workflows) to enhance fraud detection, automate investigation workflows, generate risk narratives, and improve model explainability.
  • Partnering with business and technical stakeholders to translate fraud business problems into data science solutions.
  • Work on highly-scalable ML models and algorithms in big data mining, graph modeling & other domains.
  • Work with engineering teams to implement model pipeline and deploy the service at scale.
  • Swiftly respond to system issues and deep dive into root cause analysis


What you'll bring:
  • Industry experience in building production machine learning systems at scale.
  • Experienced with languages used to manipulate data and draw insights from large data sets (e.g. Python, SQL, etc.)
  • Experience working with large data sets and distributed computing tools (PySpark/GCP/BigQuery).
  • Hands-on experience or strong familiarity with Graph Neural Networks (GNNs), graph embeddings, or large-scale graph processing frameworks.
  • Experience exploring or applying Generative AI / LLM-based approaches for decision intelligence, feature generation, workflow automation, or explainability.
  • Experience in fraud risk solutions is desirable
  • Experience in working with cross-functional product and engineering teams to understand requirements and incorporate them in the roadmap.


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...

2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America

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