FBA Inventory team is looking for a passionate, talented, and motivated Senior Economist who is a Reduced Form Causal Analysis expert to join our top-notch cross-domain science team to proactively identify new opportunities to improve the profitability of our third-party Sellers. The position offers an opportunity to apply the frontier of econometrics and economic theory to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build causal estimation models, using our world class data systems, and apply econometric theory to solve business problems in a fast-moving environment. Your will lead the science effort to learn more about Seller behaviors, estimate the effects of policies and incentives on Seller responses, design experiments to measure program impact, develop new econometric techniques, and implement science products and services to help Sellers to improve their inventory efficiency and long-term value from both Amazon’s and sellers’ perspectives by using innovative and scalable science solutions based on interdisciplinary research of operations research, machine learning, market design, econometrics, causal analysis, and data analytics. This role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate these models into production systems.
Key job responsibilities
As a member of the science team, you will play an integral part in Amazon's FBA inventory management with the following technical and leadership responsibilities:
· Apply expertise in causal modeling to develop econometric/machine learning models and design experiments to measure the value of the business and its many features
· Reviews and audits modeling processes and results for other scientists, both junior and senior.
· Identify new opportunities for leveraging economic insights and models in the FBA business and translate those directions into specific plans for economists and scientists, as well as engineering and product teams.
· Describes strategic importance of vision inside and outside of team. Identifies business opportunities, define the problem and roadmap to solve it.
· Build scalable and state-of-the art econometric solutions using state of the art tools based on large data sets
· Partner closely with senior-level Economists and Scientists at Amazon
A day in the life
In this role, you will be a technical leader in econometric modeling with significant scope, impact, and high visibility. Your solutions may lead to billions of dollars impact on either the topline or the bottom line of Amazon business. As the senior economist in the science team, you will be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. From day one, you will be working with experienced scientists, engineers, and designers who love what they do. You are expected to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. You will also collaborate with the broader decision and research science community in SCOT and Amazon to broaden the horizon of your work and mentor economists and scientists. The successful candidate will have strong quantitative modeling skills and the ability to apply econometric, statistical/machine learning, and experimental design methods to large amount of individual level data. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create scalable causal inference solutions. The candidate will need to be entrepreneurial, wear many hats, and work in a fast-paced, high-energy, highly collaborative environment. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.
About the team
Sellers are a critical part of Amazon’s ecosystem to deliver on our vision of offering the Earth’s largest selection and lowest prices. Fulfillment By Amazon (FBA) enables Sellers to provide fast and efficient deliver to their customers using Amazon fulfillment services. In 2020, Sellers enjoyed strong growth using FBA shipping more than half of all products offered on Amazon. To our consumers, FBA provides a broad and diverse inventory of products from Books, Electronics and Apparel to Consumables and beyond with many of them available with 1-Day shipping. The FBA Inventory team within the Amazon Supply Chain Optimization Technology (SCOT) organization is in charge of defining and delivering fulfillment services to our Sellers by leveraging Amazon’s expertise in machine learning, inventory optimization, big data, and distributed systems to deliver the best inventory management experiences for our FBA Sellers. We work full stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.
“Third-party sellers are kicking our first party butt. Badly. And it’s a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from $0.1 billion to $160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion. Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization? There isn’t one answer, but we do know one extremely important part of the answer: We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers.”
—Jeff Bezos, 2018 Letter to Shareholders
• PhD in Economics.
· 4+ years of experience in academic research, industry, or economic consulting.
· Strong background in statistics methodology, applications to business problems, and/or big data.
· Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, deep neural networks) to causal modeling
· Strong research track record
· Coding ability in a scripting language such as R or Python.
· Ability to work in a fast-paced business environment
· Experience communicating with senior executives
· Experienced in observational study, causal inference, causal based prediction, structural model, panel data.
· Expertise in at least of the following: STATA, R, Python, as well as SQL.
· Effective verbal and written communications skills with ability to communicate relevant scientific insights from data to senior business leaders, financial analysts, and product managers
· Ability to work effectively within an interdisciplinary science team of economists, applied scientists, software engineers, and data engineers
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.