(USA) Senior Manager, Data Science

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.

ㅤ

ㅤ

ㅤ

ㅤ

‎