Senior Applied Scientist, Amazon Stores Economics & Science (SEAS)

Amazon•Seattle, WA

About The Position

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. Distributed Optimization Team within SEAS tackles with complex, cross organizational, and multi-disciplinary supply chain problems. We are team of passionate Applied Scientists, Research Scientists, and Economists collaborating to uncover, formulate, and solve big bet issues for broader Stores organization. We are seeking to add another member to our team who thrives in inter-disciplinary, ambiguous, and high visibility environments. Key job responsibilities The successful candidate will be expected to lead end-to-end technical initiatives from research to production, build and deploy large-scale optimization systems, and translate complex business problems into mathematical frameworks. They should have a strong publication record in top-tier conferences/journals (INFORMS, EC, ICML, etc.) and experience mentoring junior scientists and coordinating cross-functional projects. Technical expertise must include deep knowledge of operations research and optimization methods, hands-on experience with machine learning and statistical modeling, proficiency in market design, and a strong background in algorithm development and implementation. Leadership responsibilities include driving technical strategy and roadmap for complex initiatives, influencing senior stakeholders and shaping technical direction, mentoring junior scientists and fostering team growth, and collaborating effectively across functions to deliver business impact.

Requirements

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
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.

Responsibilities

Lead end-to-end technical initiatives from research to production
Build and deploy large-scale optimization systems
Translate complex business problems into mathematical frameworks
Drive technical strategy and roadmap for complex initiatives
Influence senior stakeholders and shaping technical direction
Mentor junior scientists and fostering team growth
Collaborate effectively across functions to deliver business impact

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

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