Position Summary... What you'll do... The Mission The Walmart Last Mile team is shifting from reactive tracking to proactive resolution. We are building an autonomous Recommendation Agent capable of detecting anomalies, diagnosing root causes via Causal AI, and prescribing actions to save the customer experience. We are seeking a Senior Manager, Data Science to serve as the Technical Lead for this initiative. You will be a high-impact Individual Contributor (IC) who architects the system and sets the engineering standard for the team. You won't just build models; you will define how we build, test, and monitor them. The Role This is a Player-Coach role. You will own the system architecture and mentor senior data scientists. You are the "Code Guardian"—ensuring that the team’s output isn't just scientifically sound but is also production-grade code that is tested, versioned, and monitored. What You Will Do Architect the System Strategy: Define the end-to-end framework for our proactive agent, deciding how we integrate Anomaly Detection, Causal Inference, and Forecasting into a cohesive system. Lead Code Quality & Reviews: Act as the gatekeeper for the codebase. You will conduct rigorous code reviews, enforce strict Git management workflows (branching strategies, PRs), and mandate comprehensive unit and integration testing. Model Observability: Design and implement ML Monitoring frameworks to track model performance, data drift, and concept drift in real-time. You ensure the agent doesn't silently fail when the world changes. Technical Mentorship: Lead the team through design docs and methodology selection. You will elevate the team's engineering maturity, moving them from "notebook scripts" to modular, deployable packages. Drive Causal Innovation: Spearhead the application of Causal AI to ensure our agents understand why failures happen, moving the team beyond simple correlation. Hands-On Development: Roll up your sleeves to write high-performance Python and PySpark code for the most complex components of the recommendation engine.
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Job Type
Full-time
Career Level
Mid Level