Data Scientist, Labs, SCOT Forecasting and Labs

Amazon • Bellevue, WA

1d • Onsite

About The Position

At Amazon, our SCOT Labs team owns and operates the experimentation platform that powers randomized controlled trials (RCTs) across Supply Chain Optimization Technologies (SCOT). We are the scientific gatekeepers for policy updates that govern how Amazon buys, stores, and moves billions of units of inventory worldwide. This is not traditional A/B testing: we are building the infrastructure and methodology to causally evaluate complex and interconnected supply chain interventions.

Our platform runs experiments that span millions of products and hundreds of fulfillment nodes simultaneously, measuring the real-world impact of policy changes on inventory health, customer experience, and operational cost. We are also advancing the science of causal inference in supply chain settings by developing novel approaches to treatment effect estimation, interference modeling, and emulation techniques that allow us to assess policy impact faster and more accurately than ever before.

The experiments you design and the methods you build here will directly determine which policies ship to production. These decisions influence hundreds of millions of dollars in weekly inventory investments, labor allocation for tens of thousands of associates, and Amazon's overall supply chain efficiency. Beyond operational impact, this team pushes the frontier of causal experimentation methodology and contributes to the broader scientific community with publications at top venues.

If you are a scientist who wants to shape how one of the world's largest supply chains makes decisions — solving causal inference challenges in real-world settings no academic lab or startup can replicate — this is the team for you.

Requirements

• 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of data scientist experience
• Bachelor's degree

Nice To Haves

• Master's degree, or PhD
• Natural curiosity and desire to learn

Responsibilities

• Partner with customer teams to design rigorous large-scale experiments (such as randomized controlled trials and quasi-experiments) to evaluate policy updates and model improvements across millions of products, hundreds of fulfillment nodes, and diverse business contexts
• Lead the end-to-end experimentation lifecycle, from hypothesis formulation through analysis and stakeholder alignment, to inform production rollout decisions
• Advance causal inference methodology for supply chain settings, including treatment effect estimation, interference modeling, and emulation techniques that accelerate policy evaluation
• Build and maintain production-grade experimentation infrastructure and analytical tools using Python, SQL, Scala, and related technologies
• Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform experimental design and policy development
• Develop and scale supply chain emulation systems that model inventory dynamics end to end, enabling rapid offline evaluation of policy changes across millions of products without the cost and latency of live experiments
• Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
• Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level