Principal, Data Scientist

Walmart · Retail · Sunnyvale, CA

Principal Data Scientist at Walmart focused on building cutting-edge systems for product discovery in e-commerce. This involves analyzing large datasets, designing, improving, and deploying ML models for search relevance, product discovery, and personalization using techniques in information retrieval, NLP, and computer vision. The role emphasizes applying ML ranking algorithms and building predictive models at scale.

What you'd actually do

  1. Applying machine learning ranking algorithms to maximize the relevance of search system and minimize risks.
  2. Building, validating, testing and deploying predictive models using machine learning techniques to explain or predict behavior and solve a variety of business and engineering problems.
  3. Identifying, collecting, and exploring the right data used for predictive modeling and algorithm development.
  4. Performing and leading developments using machine learning techniques in one or more of the key areas like natural language processing, computer vision, information retrieval, entity recognition, product classification, and recommender system.

Skills

Required

  • Machine learning
  • Information retrieval
  • Natural language processing (NLP)
  • Computer vision
  • Data cleaning
  • Data preparation
  • Featurization
  • Feature selection
  • Working with large data sets
  • Python
  • Java
  • Scala
  • Effective communication
  • Interpersonal skills
  • Teamwork skills
  • Ability to handle multiple concurrent projects
  • Ability to work independently
  • Ability to work in teams
  • Ability to work in a fast-paced and deadline driven environment
  • Master’s degree in Computer Science, Statistics, Artificial Intelligence, Operations Research, Mathematics, Electrical Engineering, Computational Linguistics or related fields

Nice to have

  • TensorFlow
  • PyTorch
  • Spark
  • Hadoop
  • Ph.D. in Computer Science, Statistics, Artificial Intelligence, Operations Research, Mathematics, Electrical Engineering, Computational Linguistics or related fields

What the JD emphasized

  • machine learning field with a deep understanding of machine learning and interest in applying it at scale
  • data cleaning, preparation, and featurization and selection techniques
  • Python, Java or Scala and the ability to write reusable and efficient code to automate machine learning pipeline and data processes

Other signals

  • end-to-end ownership of building cutting-edge systems
  • analyzing massive datasets
  • designing complex machine learning models
  • improving their accuracy and performance
  • deploying these solutions
  • machine learning, information retrieval, natural language processing (NLP), and computer vision
  • applying machine learning ranking algorithms
  • building, validating, testing and deploying predictive models
  • performing and leading developments using machine learning techniques