Research Scientist II, FinAuto-GREF

Are you passionate about solving large-scale optimization and machine learning problems that directly improve how Amazon operates The FinAuto team is hiring a Research Scientist to support GREF Amazons Global Real Estate and Facilities organization. GREF is responsible for managing Amazons workplace facilities transportation and related operational services across a large and complex global footprint.

This role offers a unique opportunity to work on science problems where Operations Research forecasting machine learning and decision optimization come together. Example problem areas include optimizing employee cab routes forecasting transportation demand improving facility capacity planning optimizing vendor and resource allocation reducing operational cost improving service reliability and building scalable decision systems for real-world planning problems.



Key job responsibilities
As a Research Scientist you will translate ambiguous business problems into structured mathematical and scientific solutions. You will work with business product engineering and operations teams to define the problem identify the right modeling approach build scalable algorithms and help productionize solutions that influence operational decisions. The ideal candidate will have strong depth in Operations Research applied mathematics optimization statistics and machine learning along with the ability to operate independently in a fast-moving environment.

This role is well suited for a scientist who wants to work on practical high-impact problems with large-scale data complex constraints and measurable business outcomes.

- PhD or Masters degree and 4 years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets

- Knowledge of R MATLAB Python or similar scripting language
- Experience with agile development
- Experience building web based dashboards using common frameworks

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