(usa) Director, Data Science

Walmart Walmart · Retail · Bentonville, AR

Seeking a Director of Data Science & Machine Learning to lead strategy, development, and delivery of next-generation Price Recommendation solutions. This role involves managing a team of Data Scientists and ML Engineers to build AI/ML products for pricing decisions, customer value, and business performance at scale. Responsibilities include defining roadmaps, influencing strategy, partnering with cross-functional teams, and ensuring successful delivery of high-impact pricing solutions. Technical leadership in areas like demand forecasting, price elasticity, causal inference, recommendation systems, reinforcement learning, optimization, and experimentation is expected.

What you'd actually do

  1. Define and own the multi-year vision and roadmap for Price Recommendation capabilities aligned with business objectives.
  2. Lead, mentor, and grow a team of Data Scientists, Machine Learning Engineers, and technical managers.
  3. Partner with Product Management to define priorities, investment decisions, and roadmap execution.
  4. Build strong partnerships with Product, Engineering, Merchandising, Finance, Operations, and Executive Leadership.
  5. Lead end-to-end delivery of ML products from ideation through production deployment and post-launch measurement.

Skills

Required

  • Data Science
  • Machine Learning
  • Leadership
  • Product Management
  • Stakeholder Management
  • Roadmap Definition
  • Team Management
  • Demand Forecasting
  • Price Elasticity Modeling
  • Causal Inference
  • Recommendation Systems
  • Reinforcement Learning
  • Optimization
  • Experimentation
  • A/B Testing
  • Responsible AI

Nice to have

  • AI
  • ML Engineering
  • Innovation
  • Scalable Solutions
  • Production Deployment
  • Model Monitoring
  • ML Platforms

What the JD emphasized

  • lead the strategy, development, and delivery of next-generation Price Recommendation solutions
  • AI and ML products that improve pricing decisions
  • exceptional leadership, product thinking, and stakeholder management skills
  • define the long-term roadmap
  • influence executive strategy
  • partner closely with Product, Engineering, Merchandising, and Business teams
  • ensure successful delivery of high-impact pricing solutions
  • lead, mentor, and grow a team of Data Scientists, Machine Learning Engineers, and technical managers
  • Foster a culture of innovation, ownership, collaboration, and continuous learning
  • partner with Product Management to define priorities, investment decisions, and roadmap execution
  • Drive prioritization across multiple initiatives while effectively managing dependencies, risks, and trade-offs
  • Build strong partnerships with Product, Engineering, Merchandising, Finance, Operations, and Executive Leadership
  • Translate complex technical concepts into clear business outcomes for senior leadership
  • Align multiple organizations around common goals and execution plans
  • Serve as the primary data science leader for pricing initiatives across the organization
  • Lead end-to-end delivery of ML products from ideation through production deployment and post-launch measurement
  • Ensure solutions are scalable, reliable, explainable, and measurable
  • Establish operational excellence through strong execution, governance, and engineering best practices
  • Define success metrics and continuously improve model performance and business impact
  • Provide technical direction on machine learning methodologies including: Demand forecasting, Price elasticity modeling, Causal inference, Recommendation systems, Reinforcement learning, Optimization, Experimentation and A/B testing
  • Promote best practices in model development, validation, monitoring, and responsible AI
  • Guide architectural decisions to ensure scalable and reusable ML platforms

Other signals

  • leading a team of data scientists and ML engineers
  • building AI and ML products that improve pricing decisions
  • define the long-term roadmap
  • partner closely with Product, Engineering, Merchandising, and Business teams
  • ensure successful delivery of high-impact pricing solutions
  • lead end-to-end delivery of ML products from ideation through production deployment and post-launch measurement
  • guide architectural decisions to ensure scalable and reusable ML platforms