Economist - Marketing Measurement

Job ID: 1540603 | Services LLC


Amazon’s High Value Messaging (HVM) Analytics team (part of Customer Behavior Analytics org) is looking for an experienced and motivated Economist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable scientific models to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. We are looking for a thought leader that has an aptitude for delivering customer-focused solutions and who enjoys working on the intersection of Causal Inference, Big-Data analytics, and Machine/Deep Learning.

A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You will apply your econometrics expertise to identify opportunities for further research and to provide insights that drive larger initiatives. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.

The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.

The main responsibilities for this position include:
· Apply your expertise in causal modeling and ML to develop systems that describe how Amazon’s marketing campaigns impact customers’ actions
· Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions
· Improve upon and simplify our existing solutions and frameworks
· Review and audit modeling processes and results from other economists/scientists, both junior and senior
· Work with marketing leadership to align our measurement plan with business strategy
· Formalize assumptions about how our models are expected to behave and explain why they are reasonable
· Identify new opportunities that are suggested by the data insights
· Bring a department-wide perspective into decision making
· Develop and document scientific research to be shared with the greater science community at Amazon


· PhD degree in Economics, Quantitative Marketing, Finance, or closely related field


· Experience with marketing measurement and/or building production level systems for causal inference
· Experience working with big data and machine/deep learning frameworks
· Experience with Spark and AWS services including S3 and EMR
· Experience communicating results and business impact of analytical deep dives to senior leadership
· Ability to think strategically, and also stay on top of tactical execution
· Applicants with considerably more experience, including mid-career, are also strongly encouraged.
· 1+ years of working experience in building econometrics and/or machine learning models for business applications
· Hands on experience with at least one of the following: Python, Spark (or similar languages)
· Strong written and verbal communication skills

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