ADCI
Technology
ResearchScientistII,FinAuto-GREF
Neural analysis suggests this role is
optimal for Mid candidates.
“Research Scientist II, FinAuto-GREF at ADCI. Skills: Optimization, Machine learning, Operations Research. Translate business problems into solutions. Define problems with teams”
What You'll Achieve.
Improve Amazon operations; Reduce operational cost; Improve service reliability
Industry & Context.
Problem solving
What They're Looking For.
Must Have
Master's degree and 4+ years quantitative field research experience, Experience investigating scientific principles feasibility, Experience analyzing experimental and observational data
Nice to Have
Knowledge of R, MATLAB, Python, Experience with agile development, Experience building web based dashboards
What You'll Do.
Translate business problems into solutions
Define problems with teams
Identify modeling approach
Build scalable algorithms
Productionize solutions
Influence operational decisions
How You'll Work.
Team & Collaboration
Business teams; Product teams; Engineering teams; Operations teams
Full Job Description
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, Amazon’s Global Real Estate and Facilities organization. GREF is responsible for managing Amazon’s 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. Basic Qualifications: - PhD, or Master's 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 Preferred Qualifications: - Knowledge of R, MATLA
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