How do you design and provide right incentives for millions of sellers that inbound and ship billions of customer orders? How do you measure sellers' response to /causal impacts of capacity control policies we implemented at Amazon using the state-of-the-art econometric techniques? How do you optimize Amazon’s third-party supply chain using new ideas never implemented at this scale to benefit millions of customers worldwide? How do you design and evaluate seller assistance to drive their success? If these type of questions get your mind racing, we want to hear from you.
Supply Chain Optimization Technologies (SCOT) optimizes Amazon’s global supply chain end to end and build systems to deliver billions of products to our customers’ doorsteps faster every year while saving hundreds of millions of dollars using economics, operational research, machine learning, and scalable distributed software on the Cloud. Fulfillment by Amazon (FBA) is an Amazon service for our marketplace third party sellers, where our sellers leverage our world-class facilities and provide customers Prime delivery promise on all their goods.
We are looking for the next outstanding economist to join our interdisciplinary team of data scientists, research scientists, applied scientists, economists. The ideal candidate combines econometric acumen with strong business judgment. You have versatile modeling skills and are comfortable extracting insights from observational and experimental data. You translate insights into action through proofs-of-concept and partnerships with engineers and data scientists to productionize. You are excited to learn from and alongside seasoned analysts, scientists, engineers, and business leaders. You are an excellent communicator and effectively translate business ideas and technical findings into business action (and customer delight).
Key job responsibilities
- Provide data-driven guidance and recommendations on strategic questions facing the FBA leadership
- Design and implement V0 models and experiments to kickstart new initiatives, thinking, and drive system-level changes across Amazon
- Help build a long-term research agenda to understand, break down, and tackle the most stubborn and ambiguous business challenges
- Influence business leaders and work closely with other scientists at Amazon to deliver measurable progress and change
- Experienced in STATA, Python, and SQL.
- Experience in academia, private sector, consulting or government
- Working experience in Stata, R, Matlab, and/or Python
- Experience applying empirical techniques in reduced-form causal analysis, empirical industrial organization, and/or machine learning
- Ability to distill and communicate relevant scientific insights to senior business leaders
- Strong background in statistics methodology, applications to business problems, and/or big data.
- Ability to communicate complex science concepts, methods, and results/insights to leadership, business stakeholders, and partners in an intuitive and effective way.
- Ability to work in a fast-paced business environment.
- Preferred specialties in Reduced Form Causal Analysis and Machine Learning.
- Hands on expertise with SQL and Python.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.