Applied Scientist, Labs, SCOT Forecasting and Labs
Based in United States
Core
Design and build large-scale randomized controlled trials and causal inference methods to evaluate supply chain policy updates across millions of products and fulfillment nodes.
Role type
Senior Applied Scientist (Causal Inference & Experimentation)
Builds
Production-grade experimentation infrastructure, estimators, and supply chain emulation systems
Domain
Supply Chain Optimization, Causal Inference, Large-scale Experimentation
Deliverable
production ML models
Required skills
Causal inference, treatment effect estimation, randomized controlled trials, interference modeling, Python, SQL, Scala, Java/C++, algorithms and data structures, numerical optimization, parallel and distributed computing
Preferred skills
Unix/Linux, professional software development
Technologies
Python, SQL, Scala, Java, C++