Key job responsibilities
The successful candidate will lead large-scale science initiatives from research to production and translate complex business problems into mathematical frameworks. They will design and implement large-scale optimization algorithms for complex supply chain and marketplace problems, and design incentive-compatible mechanisms for marketplace challenges including auction design, matching algorithms, and pricing strategies.
The ideal candidate will have a strong publication record in top-tier conferences/journals (INFORMS, EC, WINE, ICML, NeurIPS, etc.) and experience coordinating cross-functional projects. They should have hands-on experience building science solutions that apply optimization techniques to mechanism design problems (e.g., optimal auction design, welfare maximization under constraints), with expertise in statistical learning and algorithm development.
Leadership responsibilities include driving technical strategy and roadmap for complex initiatives, influencing senior stakeholders and shaping technical direction, mentoring 2-4 junior scientists and fostering team growth, and collaborating effectively across functions to deliver measurable business impact.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or PhD and 5+ years of industry or academic research experience
- Experience in at least one of the related science disciplines (optimization - LP, MIP, statistics, machine learning, process control, combinatorial optimization)
- Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
- Experience effectively communicating complex concepts through written and verbal communication
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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, CA, Mountain View - 192,200.00 - 260,000.00 USD annually
USA, NY, New York - 183,800.00 - 248,700.00 USD annually
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually