Key job 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
A day in the life
You might start the morning reviewing results from a randomized controlled trial running across millions of products, digging into causal estimates and designing the next iteration. Later, you could be designing an experiment with a partner team where interference is unavoidable: treated and control units share fulfillment networks and inventory pools, and you need a credible strategy despite the spillover effects.
You'll build supply chain emulation systems that replicate inventory dynamics end to end, write code in Python, Scala, and SQL at a scale most scientists never encounter, and collaborate with scientists, engineers, and business teams across SCOT. Your research has a real chance of being published at top venues.
The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships, this is where you do it.
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- Master's degree, or PhD
- Natural curiosity and desire to learn
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 136,000.00 - 184,000.00 USD annually
