(USA) Senior, Data Scientist

Walmart•Sunnyvale, CA

5d•$117,000 - $234,000•Onsite

About The Position

As a Senior Data Scientist at Walmart, you will leverage advanced analytical techniques and data science expertise to deliver actionable insights that drive strategic business decisions. This role involves identifying and sourcing relevant data, developing and validating predictive models, and deploying scalable solutions aligned with business objectives. You will collaborate across functions to translate complex data into clear visualizations and recommendations, while mentoring team members and ensuring adherence to data quality and governance standards. Your contributions will support Walmart’s commitment to innovation, operational excellence, and customer-centric growth. About the team: The Applied AI Search & Personalization team develops advanced machine learning solutions to improve product discovery and deliver customized shopping experiences. The team focuses on large-scale systems including query understanding, retrieval, ranking, recommendations, personalization, and Generative AI. Combining innovative AI research with strong engineering, the team tackles complex challenges globally, enhancing customer engagement and business growth. Members collaborate to design and deploy scalable models that support Walmart’s mission to provide efficient, tailored services worldwide, driving measurable improvements in conversion rates and overall customer satisfaction.

Requirements

Extensive experience in data science, machine learning, and predictive modeling with proficiency in Python and SQL.
Strong knowledge of statistical methods, exploratory data analysis, and feature engineering to develop robust analytical models.
Expertise in data visualization tools and techniques to effectively communicate complex insights to stakeholders.
Proven ability to identify and source appropriate data, ensuring data quality and alignment with business requirements.
Familiarity with model deployment, scalability, and validation techniques to support production environments.
Solid understanding of business domains and ability to translate business needs into data-driven solutions.
Experience mentoring junior associates and collaborating cross-functionally to achieve strategic objectives.
Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field.
Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field.
5 years' experience in an analytics or related field.

Nice To Haves

Data science, machine learning, optimization models
Master’s degree 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)
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.
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.

Responsibilities

Identify and source relevant data from multiple business domains, ensuring data quality and suitability for analysis.
Develop, test, and deploy advanced analytical models using statistical and machine learning techniques to address complex business challenges.
Perform exploratory data analysis, feature engineering, and data visualization to generate actionable insights for stakeholders.
Collaborate with cross-functional teams to translate business requirements into data-driven solutions aligned with strategic objectives.
Mentor junior associates on modeling techniques and best practices, fostering continuous improvement and knowledge sharing.
Support scalability and sustainability of models in production environments, ensuring robust performance and compliance with standards.