Principal, Data Scientist

Walmart Walmart · Retail · Bangalore, KA, India

Principal Data Scientist role at Walmart focused on building and deploying AI/ML, NLP, and GenAI models, including fine-tuning LLMs, for product catalog optimization in a retail environment. The role involves R&D, leading teams, and partnering with product and engineering leaders.

What you'd actually do

  1. Formulating a strategy and roadmap to design, develop, and deploy AI/ML, NLP and GenAI models into production environments with a focus on reliability and scalability.
  2. Build/Fine-tune state-of-the-art large language models (LLMs) using Walmart's massive datasets.
  3. Lead and inspire a team of scientists and engineers solving AI/ML problems through R&D while pushing the state-of-the-art to drive innovation at scale
  4. Executing full life cycle of projects through planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners.
  5. Partner closely with Product and engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, machine learning prototypes, and the strategic importance of AI initiatives.

Skills

Required

  • Bachelors/Masters/PhD from a reputed institution
  • Minimum of 12+ years of data science experience
  • Demonstrated history of technology leadership
  • Strong hands-on experience
  • Proven records of scientific publications or intellectual property generation
  • Hands-on experience in Large Language Models
  • Multimodal Vision Language Models
  • Recommender Systems
  • Computer Vision
  • Optimization Models
  • Reinforcement Learning
  • Strong programming skills across data science, big data and ML engineering stack
  • Strong communication skills
  • High ownership and commitment
  • Experience with Ecommerce domain

What the JD emphasized

  • reliability and scalability
  • state-of-the-art large language models
  • massive datasets
  • pushing the state-of-the-art
  • drive innovation at scale
  • full life cycle of projects
  • stakeholder management
  • communication to cross-functional partners
  • accelerate innovations
  • strategic importance of AI initiatives
  • AI/ML model development
  • compliance with model and data governance standards
  • scientific publications
  • intellectual property generation
  • Large Language Models
  • Multimodal Vision Language Models
  • Recommender Systems
  • Computer Vision
  • Optimization Models
  • Reinforcement Learning
  • strong programming skills
  • data science, big data and ML engineering stack
  • high ownership and commitment
  • Ecommerce domain

Other signals

  • Generative AI
  • Large Language Models
  • ML Engineering
  • Production Deployment
  • Retail Use Cases