Staff, Data Scientist - Machine Learning Platform

Position Summary :

Is this the next step in your career Find out if you are the right candidate by reading through the complete overview below.

As a Staff, Data Scientist, we invite you to become part of a team that is dedicated to the development of data-driven models and services.

Our primary focus is on driving high-quality demand from a plethora of digital platforms, including Google, Bing, Facebook, and Pinterest, to Walmart's E-Commerce sites.

About Team : Machine Learning Platform Team

Our team works closely with our US stores and 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. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.

Walmart's Advertising Technology group enables the connection between supplier brands and retail shoppers at unprecedented scale.

We are a highly motivated group of engineers and data scientists, working in an agile group to solve sophisticated and high impact problems.

What You'll Do :

• The development and deployment of a foundational AI layer along with Gen AI models for online inferencing. This is crucial for supporting applications such as Ads moderation, social commerce, etc.
• The development and maintenance of a robust, scalable machine learning platform, facilitating end-to-end machine learning operations from model development and versioning to deployment.
• The creation, deployment, and maintenance of high-quality web-based dashboard systems to draw visual insights from our ever-expanding dataset, monitor machine learning models, and evaluate model performance via A / B testing.
• The development, testing, and deployment of big-data and machine learning pipelines, encompassing data ingestion, model production, and visualization.
• Efficient management of public cloud services, using public cloud tools and resources to scale our storage and computation capabilities on the Google Cloud Platform.

What You'll Bring :

• A solid understanding of data structures and algorithms.
• Proficiency in at least one programming language such as Python, Java, C++, or JavaScript.
• Extensive knowledge and experience in distributed inferencing in GPUs, LLM serving framework, and PyTorch / Tensorflow, etc.
• Knowledge and experience in Linux, public cloud computing, Docker, and Kubernetes.
• Experience in the development of REST API services.

Minimum Qualifications :

Outlined below are the required minimum qualifications for this position :

• Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 4 years' experience in an analytics related field.
• Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 2 years' experience in an analytics related field.
• 6 years' experience in an analytics or related field.

As permitted by applicable law, provide evidence of full vaccination as defined by CDC guidelines OR secure approval of medical or religious accommodation for the vaccination mandate.

Preferred Qualifications :

Outlined below are the optional preferred qualifications for this position :

• 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.
• Using open source frameworks (for example, scikit learn, tensorflow, torch).
• Knowledge of accessibility best practices and experience in creating inclusive digital experiences.

Primary Location :

680 West California Avenue, Sunnyvale, CA 94086-4834, United States of America

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