Are you passionate about developing new state-of-the-art measurement approaches at Petabyte scale? Do you enjoy solving some of the most challenging economic questions in the technology industry? Amazon Advertising is one of Amazon’s fastest growing businesses, and we are leveraging our unique data, the latest machine learning methods and big data technologies to better understand how advertising influences customer behavior. We have a world-class platform and are focused on building in-house technology to deliver on a growing number of Amazon’s owned marketing programs. We operate on a massive scale and are continuously innovating to expand the problems we solve.
We are seeking a talented, causal economist to join our team and help us deliver novel measurement solutions to understand the impact of our marketing activities on customer behavior. This role will impact billions of dollars in investment decisions and provide insights for decision-making by dozens of Amazon’s most strategic businesses. What makes us unique is our unprecedented volumes of feature-rich data, our compute power, and our world-class engineering systems; these factors create an opportunity for us to set new industry standards in marketing measurement and customer insight. Our economist will apply econometric theory to build models and prototypes that lead to scalable implementations in partnership with engineering teams. We offer the opportunity to work with data of unparalleled quality, apply rigorous econometric approaches, and work with some of the most talented econometricians and engineers in the industry.
As a successful candidate, you will be a self-starter, entrepreneurial, comfortable with ambiguity, and with a strong technical acumen. You will be able to formalize problem definitions from ambiguous requirements, assess if existing academic research can be extended, and propose novel solutions to non-standard problems. You will be able to solve problems by developing new techniques to process large data sets, using causal inference, machine learning, and working with teams to automate models at scale. You will be effective communicating complicated concepts clearly to business leaders and other scientists, and comfortable building, estimating, and defending causal statistical models. This position is unique in its potential for visibility and impact within Amazon.
· PhD in Economics.
· 2+ years of postdoctoral experience in industry, consulting, government or research.
· Programming in one or more statistics-oriented languages (Stata, Python, R).
· Experience in causal inference and machine learning.
· Ability to communicate relevant scientific insights from data to senior business leaders.
· Applicants with considerably more experience, including mid-career, are also strongly encouraged.
· Experience implementing modern machine-learning methods.
· Proficiency in Spark-Scala, Py-Spark, etc.
· Experience building and bringing high impact statistical models to production, at scale.
· Experience effectively collaborating with software engineers and applied scientists.
Amazon is an Equal Opportunity Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.