Staff, Data Scientist – Gen AI and Deep Learning at Walmart
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Staff, Data Scientist – Gen AI and Deep Learning at Walmart

Company Overview

Join Walmart, a leader in retail, at their cutting-edge Global Tech division in Sunnyvale, CA. Walmart Global Tech is a hub of innovation, comprising software engineers, data scientists, cybersecurity experts, and service professionals. They pioneer groundbreaking solutions that impact millions of lives and shape the future of retail. If you’re ready to make a meaningful impact and be part of the next retail revolution, Walmart Global Tech is the place for you.

Location: Sunnyvale, CA, USA

Job Type: Full-time, Mid-Senior level

Salary Range: $143,000/yr – $286,000/yr

About the Role

Walmart’s Marketing and Advertising Data Science Team is seeking a Staff Data Scientist specializing in Generative AI and Deep Learning to drive their AI initiatives. The ideal candidate will be proficient in state-of-the-art Gen AI and Large Language Models (LLMs), capable of translating innovative concepts into impactful business applications. This role offers an exciting opportunity to work on data-driven solutions that optimize marketing and advertising strategies to connect Walmart, suppliers, and sellers with customers.

Position Summary

The Staff Data Scientist will collaborate with cross-functional teams to develop and customize deep learning-based generative models for text, images, and videos. They will leverage large language models to design AI-powered conversational assistants for advertisers and marketers. The role involves leading the development of innovative AI solutions, collaborating with engineering teams to ensure scalability and reliability, and exploring novel applications for generative AI within marketing and advertising.

Responsibilities

  • Develop and customize deep learning-based generative models for text, images, and videos.
  • Design AI-powered conversational assistants for advertisers and marketers using large language models.
  • Collaborate with engineering teams to transition AI innovations into scalable operational solutions.
  • Explore and identify novel applications for generative AI within marketing and advertising sectors.
  • Produce visuals and reports to communicate model outcomes and insights to business stakeholders.
  • Maintain academic credentials through patent applications, publications, and conference presentations.

Requirements

Education – Bachelor’s degree in Computer Science, Statistics, Data Science, Mathematics, or related field, with 4 years of experience, or Master’s degree with 2 years of experience. PhD preferred.

Experience Minimum of 4 years’ experience in analytics or related field, with a strong academic and publication record. Experience with deep learning-based generative models and large language models is required.

Skills

  • Proficiency in Python and experience with large data sets.
  • Familiarity with IT architecture frameworks and tools.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration abilities.

About Walmart Global Tech

Walmart Global Tech is a dynamic environment where innovation thrives, and every contribution makes a difference. Their hybrid work model fosters collaboration and flexibility, allowing employees to work both in-office and virtually. Walmart offers competitive compensation, including performance-based incentives, along with a comprehensive benefits package.

Benefits

Walmart offers a range of benefits, including:

  • 401(k) match
  • Stock purchase plan
  • Paid maternity and parental leave
  • Paid time off (PTO)
  • Health plans
  • And more

Equal Opportunity Employer

Walmart is committed to diversity and inclusion, valuing unique perspectives and experiences. They believe in creating an inclusive environment where all individuals are respected and valued.

How to Apply

If you’re passionate about leveraging AI to drive business innovation and want to be part of Walmart’s groundbreaking initiatives, apply now. Join Walmart Global Tech and be at the forefront of retail disruption.