Staff, Data Scientist | Machine Learning (Fraud & Risk) | Sunnyvale

Walmart•Sunnyvale, CA

1d•Onsite

About The Position

As a Staff Data Scientist, you will architect machine learning solutions for complex and ambiguous business problems, perform hands-on exploration, processing, and analysis of massive datasets, and use machine learning, deep learning, data mining, and GenAI techniques to develop scalable predictive models. You will design low-latency cloud services to host and productionize models, research advanced algorithms, communicate results through presentations, publications, and conferences, and contribute to the team's machine learning and software engineering capabilities. The team works with Walmart U.S. stores and eCommerce to improve customer experiences and support associates, stores, and merchants across products available online and in stores. Its focus areas include customer engagement, store operations, merchant tools, data science, and personalized search. This is a full-time onsite role based in Sunnyvale, California. Remote and hybrid options are not available. Immigration sponsorship is unavailable; applicants must be authorized to work for any U.S. employer without current or future visa sponsorship.

Requirements

The role summary requests a Ph.D. in a quantitative field with at least 5 years of relevant industry experience, or a Master's degree in a related quantitative discipline with at least 7 years of experience architecting, building, and deploying production machine learning solutions.
Proven expertise in data science, including predictive analytics, machine learning algorithms, and deep learning techniques.
Proficiency in programming languages such as Python and experience with data visualization tools such as Matplotlib, Plotly, Tableau, or PowerBI.
Strong knowledge of data strategy, data quality standards, and data governance principles.
Experience with big data analytics, unstructured data processing, and MLOps for model deployment and scaling.
Ability to assess, validate, and tune models using statistical methods and evaluation metrics.
Ability to translate complex business requirements into data-driven solutions and actionable insights.
Effective communication skills to present findings clearly to stakeholders and guide junior team members.
The listed minimum qualifications state one of the following: 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 those fields and 2 years of analytics-related experience; or 6 years of experience in an analytics or related field.
Must be authorized to work for any employer in the United States without current or future visa sponsorship.

Nice To Haves

Data science, machine learning, and optimization models experience.
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.
Background in creating inclusive digital experiences, including knowledge of WCAG 2.2 AA standards, assistive technologies, accessibility best practices, and Walmart accessibility standards and guidelines.

Responsibilities

Identify and source relevant data from multiple business domains and databases to support analytics initiatives.
Perform data quality assessments and ensure data integrity for accurate model development.
Develop, validate, and tune predictive models using statistical, machine learning, deep learning, and LLM techniques.
Design and implement data visualizations to communicate insights to stakeholders.
Collaborate with cross-functional teams to translate business requirements into data-driven solutions.
Deploy and monitor models in production environments, ensuring scalability and performance.
Mentor team members on analytical methods, coding best practices, and solution design.
Research advanced algorithms to solve challenging business problems.
Communicate results through presentations, publications, and internal or external conferences.