Principal, Data Scientist - Personalization

Walmart Walmart · Retail · NY NEW YORK, VIZIO SERVICES SAN FRANCISCO CA San Francisco

Lead the design and delivery of machine learning solutions for personalization and ad targeting at VIZIO. This role involves owning complex problems end-to-end, translating product needs into scalable ML models, and iterating through evaluation and experimentation. The Principal Data Scientist will also set technical standards, contribute hands-on deep learning models, and mentor other data scientists.

What you'd actually do

  1. Tackle ambiguous, high‑impact problems by translating product and business questions into well‑scoped ML and data science work.
  2. Build, evaluate, and iterate on advanced deep learning models for personalization and recommendation.
  3. Design and apply rigorous offline metrics and online experimentation frameworks to measure model and system performance.
  4. Partner closely with Product and Engineering to align on scope, tradeoffs, and execution across multiple teams.
  5. Help define best practices for modeling, experimentation, and ML development, with a focus on robustness and maintainability.

Skills

Required

  • Machine learning
  • Statistics
  • Deep learning architectures
  • Representation learning
  • Optimization
  • Model evaluation
  • Personalization
  • Recommendation systems
  • Ranking
  • Ad targeting
  • Python
  • PySpark
  • PyTorch
  • JAX
  • MLflow
  • Experimentation frameworks

Nice to have

  • PhD in Machine Learning
  • Computer Science
  • Information Technology
  • Operations Research
  • Statistics
  • Applied Mathematics
  • Econometrics
  • Publications
  • Active peer reviewer

What the JD emphasized

  • Extensive experience designing, training, and deploying machine learning models for real-world systems, particularly in personalization, recommendation, ranking, or targeting.
  • Deep technical foundations in machine learning and statistics, including experience with representation learning, deep learning architectures, optimization, and model evaluation.
  • Production Python experience, comfortable with distributed data tools such as PySpark and expertise in modern ML frameworks (e.g. PyTorch, JAX, etc.). You are opinionated about model design, training workflows, and evaluation/experimentation strategies.
  • Comfortable operating in ambiguous, technically complex problem spaces, taking ownership from initial formulation through deployment and iteration.
  • Enjoy raising the technical bar through mentorship, design reviews, and hands-on collaboration with other data scientists.

Other signals

  • personalization
  • recommendation
  • ad targeting
  • deep learning
  • experimentation