Senior, Data Scientist

Walmart is seeking a Senior Data Scientist to develop and deploy data-driven solutions that support fraud and abuse detection. This onsite role in Sunnyvale, CA focuses on applying advanced machine learning and deep learning to large-scale real-time datasets, with opportunities to deliver insights through models, dashboards, and cross-functional collaboration.

Role Summary

In this position, you will build predictive models and leverage visualization to communicate findings. You will also collaborate with product and engineering teams to improve data governance and data quality while owning fraud and abuse risk areas within a product or segment.

Responsibilities

• Design, build, and implement predictive models using high-dimensional, fast-moving real-time datasets.
• Own fraud and abuse risks in a product or segment, partnering strategically with product development teams and sharing recommendations through data storytelling.
• Apply machine learning, AI, deep learning, and data mining methods to develop robust anomaly detection models, including bot detection.
• Create data visualizations and interactive dashboards to monitor performance and share business insights internally and externally.
• Explore research opportunities, including US patent filings, to address new fraud issues and develop new tools or automate processes.

Required Qualifications

• Minimum experience: 1 years.
• Education (minimum): Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field.

Additional Requirements

• Technical expertise in machine learning, statistical analysis, and data storytelling.
• Proficiency with machine learning and data mining packages in Python.
• Experience working with large datasets and distributed computing tools; GCP/BigQuery experience is preferred.
• Programming skills in Java or JavaScript on a UNIX or Linux platform.
• Production deployment experience is preferred.
• GenAI and agentic AI experience is preferred.

Technologies

• Python, GCP, BigQuery
• Java, JavaScript
• Unix, Linux

Preferred Qualifications

• Experience with data science, machine learning, and optimization models.
• Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics.
• Successful completion of one or more assessments in Python, Spark, Scala, or R.
• Experience using open source frameworks such as scikit-learn, TensorFlow, or Torch.
• Background in creating inclusive digital experiences, including knowledge of implementing WCAG 2.2 AA, assistive technologies, and integrating digital accessibility.
• Knowledge of accessibility best practices.

Minimum Qualifications

• Option 1: Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field, plus 3 years of experience in an analytics-related field.
• Option 2: Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field, plus 1 years of experience in an analytics-related field.
• Option 3: 5 years of experience in an analytics or related field.

Benefits

• Performance-based bonus awards
• Medical, vision and dental coverage
• 401(k)
• Stock purchase
• Company-paid life insurance
• PTO (including sick leave)
• Parental leave
• Family care leave
• Bereavement
• Jury duty
• Voting
• Short-term and long-term disability
• Company discounts
• Military Leave Pay
• Adoption and surrogacy expense reimbursement
• Live Better U (Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam’s Club facilities)

Location and Compensation

• Location: Sunnyvale, CA (onsite)
• Salary: USD 108,000 - 234,000 per year

About the Team

This role supports Walmart’s fraud detection team. You will work with large volumes of business and social data generated by Walmart Inc.’s online and offline commerce. The team is cross-functional, bringing together data scientists, engineers, product managers, and business professionals across Data Science, big data, IT infrastructure, and business operations.