Staff, Data Scientist - Personalization - GenAI

Staff Data Scientist - Personalization Team - Generative AI Expertise

Position Summary:

Join the Personalization Team at Walmart, where we are devoted to creating top-tier data products. We harness state-of-the-art industrial technology to power end-to-end personalized recommendations. We're on the lookout for a Staff Data Scientist with over 5 years of industry experience in Machine Learning, specializing in Generative AI, large language models, multi-modal generative AI, retrieval augmentation, and multi-language agent pipelines.

What You'll Do:

As a Staff Data Scientist, you will:

• Lead the development and integration of data-driven product capabilities.
• Oversee team projects, providing technical support to ensure timely delivery.
• Promote adherence to MLOps and software best practices, including data and code quality testing.
• Collaborate with cross-functional teams to identify opportunities and drive innovation.
• Evaluate business cases, translating product requirements into strategies, aiding in prioritization and planning.

What You'll Bring:

To excel in this role, you should have:

• A Master’s degree in Data Science, Computer Science, or related fields, plus over 5 years of practical data science experience.
• Deep understanding of machine learning algorithms and statistics.
• Experience with Generative AI is a significant advantage.
• Industry experience in eCommerce and digital customer behavior applications.
• Proficiency in programming languages such as SQL, Python, and PySpark.
• Exceptional business acumen and problem-solving skills, with proven ability to prototype and implement complex AI solutions.
• Outstanding communication and leadership abilities.

About the Team:

Our team collaborates closely with our US stores and eCommerce business to enhance customer service through technological innovation. We support a broad range of products, from groceries to sporting goods, through various shopping channels at Walmart U.S. Our focus areas include:

• Customers
• Stores and employees
• In-store service
• Merchant tools and data science
• Search and personalization

About Walmart Global Tech:

Imagine working in an environment where a single line of code can positively impact hundreds of millions of people. At Walmart Global Tech, we are a collaborative team of software engineers, data scientists, cybersecurity experts, and service professionals. We innovate on a massive scale, redefine retail with cutting-edge technology, and empower our team members with the skills of the future. Here, you can embark on a tech career, gain new skills, and have the opportunity to make a significant impact.

Flexible, Hybrid Work:

We have adopted a hybrid working model which combines in-office and virtual work to enhance collaboration and flexibility.

Benefits:

We offer a competitive compensation package, performance-based bonuses, and an array of benefits, including:

• 401(k) match
• Stock purchase plan
• Paid maternity and parental leave
• PTO and health plans
• Various other benefits

Equal Opportunity Employer:

Walmart, Inc. is an Equal Opportunity Employer. We are committed to understanding, respecting, and valuing diversity while promoting inclusivity.

Minimum Qualifications:

Requirements for the position include:

• Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field with 4 years of experience in an analytics-related field OR
• Master’s degree in the mentioned fields with 2 years of experience OR
• 6 years of experience in an analytics or related field

Preferred Qualifications:

Ideal candidates will have experience with data science, machine learning, optimization models, and possess a PhD or equivalent experience. Proficiency in Python, Spark, Scala, or R and familiarity with open-source frameworks like Scikit-learn, TensorFlow, or Torch is highly valued. Knowledge of Web Content Accessibility Guidelines (WCAG) and a background in creating inclusive digital experiences is a plus.