Lead Data Scientist

Lead the design and development of digital twin models that accurately replicate end-to-end warehouse operations.

Ingest and structure operational data from the micro-fulfillment lab to build scalable macro-simulations capable of representing enterprise-scale environments with tens of thousands of SKUs.

Stress test operational strategies—including slotting algorithms, multi-pass picking, batching logic, and automation workflows—within simulation environments prior to production deployment.

Design, test, and deploy AI-driven decision systems directly into operational workflows.

Develop models for forecasting, labor planning, inventory optimization, task prioritization, and exception handling to improve throughput, speed, and cost efficiency.

Build lightweight, production-ready analytical tools and algorithms that improve operational performance without heavy infrastructure overhead.

Translate operational data into financial impact models, linking time-and-motion studies to margin improvement, productivity gains, and labor efficiency.

Partner with operations analysts to design robust experimental frameworks, including success criteria, measurement methodologies, and statistical validation approaches.

Analyze complex, multi-variable experiments such as inventory commingling strategies and their impact on density, availability, and fulfillment speed.