Staff, Data Scientist - Health & Wellness - Consumer Health & Data Solutions

Walmart Walmart · Retail · Sunnyvale, CA

Staff Data Scientist role focused on building ML systems for recommendations, behavioral signals, and nutrition-focused chatbot experiences within Walmart's Consumer Health & Data Solutions team. The role involves leading the design and implementation of predictive models, recommender systems, and customer segmentation, taking work from data sourcing and experimentation through evaluation and production partnership. It emphasizes collaboration with product and data engineering, owning model quality, insights, and measurable impact.

What you'd actually do

  1. Build and improve ML systems for recommendations, behavioral signals, and nutrition-focused chatbot experiences.
  2. Lead the design and implementation of predictive models, recommender systems, customer segmentation and other advanced analytics projects.
  3. Develop and execute data-driven solutions for various initiatives, such as personalized product and content recommendations, health coaching, customer segmentation in the consumer health space, and product assortment in retail space.
  4. Identify fit-for-purpose data sources, run initial data quality checks, and translate product questions into modeling approaches.
  5. Evaluate and tune models using appropriate metrics (e.g., ROC, RMSE) and robust validation practices.

Skills

Required

  • Python
  • SQL
  • BigQuery
  • recommendation systems
  • search-style problems
  • model testing
  • model tuning
  • model validation
  • production-minded measurement

Nice to have

  • deep learning
  • embeddings
  • GenAI
  • bias analysis
  • fairness metrics
  • model explainability
  • time-series modeling
  • personalization systems
  • generative AI methods
  • recommendation + generative approaches
  • Spark
  • Airflow
  • health and wellness products
  • retail
  • eCommerce
  • omnichannel domains
  • HIPAA concepts
  • Agile environment

What the JD emphasized

  • Strong applied ML background
  • Experience with recommendation and/or search-style problems beyond collaborative filtering-only approaches.
  • Demonstrated skill in model testing/tuning/validation and production-minded measurement.

Other signals

  • recommendation systems
  • chatbot capabilities
  • predictive models
  • customer segmentation
  • personalized product and content recommendations
  • health coaching