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Position Summary...

As a Senior Manager, Data Science, you will influence teams of high-performing data scientists and analysts in delivering advanced analytical solutions that drive meaningful business decisions. This is a strategic, hands-on role focused on end-to-end modeling, from exploratory data analysis to model deployment, visualization, and scaling. You will work closely with cross-functional partners to solve complex business problems using statistical modeling, machine learning, and AI. Your work will directly shape decision-making in product, marketing, finance, and operations, while mentoring the next generation of data leaders. This role is ideal for someone who thrives at the intersection of business impact, technical excellence, and team development.

What you'll do...

+ Leverage machine learning technologies such as Java, Python, Pyspark, Tensorflow, and PyTorch to design, develop, and implement high-performance, scalable applications for personalized recommendations.

+ Create robust machine learning models using structured and unstructured data sets and advanced algorithms, including Neural Networks, Regression Models, and Gradient Boosting Algorithms.

+ Collaborate with data engineers and software developers to design and implement data pipelines and architectures that support recommendations at scale.

+ Work with stakeholders across the company to understand business needs and develop data-driven solutions that drive insights and automation.

+ Communicate findings and insights to stakeholders through clear and concise reports and presentations.

+ Stay up to date with the latest developments in machine learning and apply this knowledge to improve our products and processes.

What you'll bring:

+ Education: PHD or Masters in Computer Science, Statistics or Mathematics with 3+ Years of Industry Experience.

+ Deep Understanding of Machine Learning and AI: The candidate should possess a robust understanding of various machine learning algorithms, artificial intelligence, and deep learning techniques. This includes but is not limited to neural networks, gradient boosting algorithms, reinforcement learning, and large language models. They should be able to develop models with both structured and unstructured data sets.

+ Deep understanding of reinforcement learning techniques: Candidates should have a strong background in reinforcement learning, long-term reward optimization, deep Q-learning.

+ Proficiency in Programming, SQL and Data Analysis: The candidate should be highly proficient in languages such as Java, Python, PySpark, and have experience with machine learning frameworks like Tensorflow and PyTorch. They should be capable of using these technologies to design and develop high-performance applications. Additionally, they should have strong knowledge in data analysis methods like dimensionality reduction, predictive modelling, clustering, text mining for effective feature engineering.

+ Experience in Large Scale Applied ML Model Building: The candidate should have a prior track record of successfully building, deploying, and maintaining large-scale machine learning models in a production environment. This includes handling large volumes of data, optimizing model performance, and ensuring the scalability of the solution.

+ Innovation and Problem-Solving Skills: As the role involves working with new technologies, the candidate should have the ability to innovate and solve complex problems. They should be able to adapt to new technologies quickly and find creative solutions for various business problems.

About Team:

Our team works closely with our eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, Walmart U.S. offers an extensive selection that our customers value, whether they shop online at Walmart.com, through one of our mobile apps, or in-store.

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Minimum Qualifications...

_Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.

Preferred Qualifications...

_Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications._

Data science, machine learning, optimization models, PhD 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, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a 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. The ideal candidate would have 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.

Primary Location...

815 Eleventh Ave, Sunnyvale, CA 94089-4731, United States of America

Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

Walmart, Inc. is an Equal Opportunity Employer- By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, abilities, ideas and opinions- while being inclusive of all people.