Staff, Data Scientist | Sunnyvale

Walmart•Sunnyvale, CA

23h•Onsite

About The Position

The Staff, Data Scientist will use advanced analytical techniques and data science methodologies to deliver actionable insights for strategic business decisions. The role involves sourcing and validating data, developing predictive models, and deploying scalable solutions while maintaining data quality and governance standards. The successful candidate will collaborate across functions to turn complex business challenges into data-driven solutions, mentor team members, and contribute to continuous improvement aligned with organizational goals. The role is part of Walmart’s Global Fraud data science team, which develops real-time and batch decisioning services using machine learning and deep learning to address fraud and risk. The team focuses on safe, seamless shopping experiences, proactive decisioning, operational excellence through MLOps, and effective risk management. This is a full-time, onsite role based in Sunnyvale, California. Remote and hybrid options are not available. Immigration sponsorship is not available; applicants must be authorized to work for any U.S. employer without current or future visa sponsorship.

Requirements

Ph.D. in Computer Science, Data Science, Statistics, Machine Learning, Artificial Intelligence, Mathematics, or a related quantitative field, with 5+ years of relevant industry experience; or a master's degree in a related quantitative discipline with 7+ years of experience architecting, building, and deploying machine learning solutions in production.
Proficiency in predictive analytics, machine learning algorithms, and advanced statistical methods for developing and validating robust models.
Strong programming skills in Python.
Experience with data visualization tools such as Matplotlib, Plotly, or Tableau.
In-depth understanding of data strategy, including data quality standards, governance, and scalable data storage solutions.
Ability to translate complex business requirements into data-driven solutions and actionable insights.
Experience with exploratory data analysis, feature engineering, and production model deployment.
Knowledge of SQL and NoSQL database technologies for data sourcing and management.
Excellent communication skills for presenting technical findings clearly to business stakeholders.
Must be authorized to work for any employer in the United States without current or future visa sponsorship.

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 and WCAG 2.2 AA standards, assistive technologies, and digital accessibility best practices.

Responsibilities

Identify and source relevant data from multiple business domains and distributed data stores for analytics initiatives.
Assess data quality and ensure data is fit for purpose and aligned with business requirements.
Develop and validate predictive models using advanced statistical and machine learning techniques.
Create data visualizations to communicate insights to stakeholders.
Collaborate with cross-functional teams to translate business needs into data-driven solutions and strategies.
Deploy and monitor models in production environments, ensuring scalability and performance.
Mentor team members on analytical methods, coding best practices, and data storytelling.