(usa) Senior Manager, Data Science

Walmart · Retail · Bentonville, AR

Senior Manager, Data Science role at Walmart focused on architecting and implementing Agentic AI workflows for a probabilistic Media Mix Model (MMM) powered by Bayesian statistics. The role involves pioneering Bayesian MCMC MMM, developing multi-agent systems for measurement lifecycle automation, driving probabilistic forecasting, integrating causal insights, and scaling models to production.

What you'd actually do

  1. Design, implement, and productionize a scalable, Bayesian Hierarchical MMM framework (using tools like PyMC). This includes rigorous feature engineering, defining priors, implementing sophisticated MCMC sampling techniques, and developing robust methods for handling time-varying effects, diminishing returns, and competitive factors.
  2. Develop and deploy multi-agent systems (Agentic AI) to automate the entire measurement lifecycle. This involves automating data ingestion and cleaning, model version control, adaptive prior selection, and dynamic insight generation from the MMM results.
  3. Utilize the full posterior distribution from the Bayesian models to generate probabilistic forecasts and comprehensive scenario simulations, enabling Marketing and Finance teams to make data-driven, risk-aware investment decisions.
  4. Integrate MMM output with other causal inference models (e.g., A/B tests, Geospatial Experiments, uplift models) to create a unified, holistic view of marketing performance and decompose brand vs. sales effects.
  5. Partner closely with Engineering teams to transition models from research prototypes to highly reliable, performant, and automatically updating production systems that serve real-time investment recommendations to marketing platforms.

Skills

Required

  • Advanced statistical expertise
  • Full-stack machine learning engineering
  • Strategic leadership
  • Bayesian statistics
  • Markov Chain Monte Carlo (MCMC) methods
  • PyMC
  • Agentic AI workflows
  • Generative AI systems
  • LLMs
  • Multi-agent frameworks
  • Diverse machine learning algorithms
  • Deep Learning
  • PyTorch/TensorFlow
  • Reinforcement Learning concepts
  • PhD or Masters in Computer Science, Statistics, Mathematics, or a highly quantitative field
  • 5+ years of relevant industry experience

Nice to have

  • Data science
  • Machine learning
  • Optimization models
  • PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics
  • Python
  • Spark
  • Scala
  • R
  • Supervisory experience
  • Using open source frameworks (for example, scikit learn, tensorflow, torch)

What the JD emphasized

  • Agentic AI workflows
  • Bayesian MCMC MMM
  • Agentic AI
  • causal

Other signals

  • Agentic AI workflows
  • Bayesian Hierarchical MMM
  • Probabilistic Forecasting
  • Causal Inference