(USA) Staff, Data Scientist

Walmart • Bentonville, AR

12h • Onsite

About The Position

As a Staff Data Scientist at Walmart, you will use advanced analytical techniques and machine learning to turn complex data into actionable business insights. You will contribute expertise in data strategy, model development, validation, and deployment to support business decisions. The role involves collaborating across functions to identify data sources, assess data quality, and create visualizations that clearly communicate findings. Your work will support innovation and operational excellence in a dynamic retail environment.

The team combines data science and computer vision to advance safety and security initiatives, including fraud prevention, threat detection, and digital risk management. It uses cloud transformation, predictive analytics, machine learning, and data visualization to improve decision-making and operational reliability. Collaboration and continuous improvement support accurate, sustainable solutions aligned with Walmart’s strategic objectives.

The position offers an annual salary range of $110,000 to $220,000, with additional compensation that may include annual or quarterly performance bonuses and, for certain positions, stock.

Requirements

• One of the following qualification paths: a bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or a related field and 4 years of experience in an analytics-related field; a master’s degree in one of these fields and 2 years of analytics-related experience; or 6 years of experience in an analytics or related field.
• Expertise in predictive analytics and machine learning algorithms for developing and validating robust models.
• Proficiency in Python programming and data visualization tools such as Matplotlib, Plotly, or Tableau.
• Strong understanding of data strategy, including data quality, governance, and scalable data storage solutions.
• Experience identifying and sourcing relevant business data from SQL and NoSQL databases.
• Ability to translate complex business requirements into analytical models and actionable insights.
• Skill in model assessment and continuous model improvement for production deployment.

Nice To Haves

• Experience in data science, machine learning, or optimization models.
• Ph.D. 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.
• Knowledge of inclusive digital experiences, WCAG 2.2 AA standards, assistive technologies, and digital accessibility best practices.

Responsibilities

• Identify and source relevant data from multiple business domains and databases to support analytics initiatives.
• Perform data quality assessments and ensure data is suitable for modeling and analysis.
• Develop, validate, and tune predictive models using advanced statistical and machine learning techniques.
• Translate complex business problems into data-driven solutions aligned with strategic objectives.
• Create clear, impactful data visualizations and presentations tailored to stakeholder needs.
• Collaborate with cross-functional teams to deploy scalable models and monitor performance in production.
• Mentor junior team members on analytical methods, coding best practices, and data storytelling.

Benefits

• Medical, vision, and dental coverage.
• 401(k), stock purchase, and company-paid life insurance.
• Paid time off, including sick leave, parental leave, family care leave, bereavement leave, jury duty, and voting leave.
• Short-term and long-term disability.
• Company discounts.
• Military Leave Pay.
• Adoption and surrogacy expense reimbursement.
• Live Better U, a Walmart-paid education benefit program for eligible associates, covering tuition, books, and fees for qualifying programs.
• Performance-based bonuses and, for certain positions, stock.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior