Economist - II, Amazon Hub

• PhD in Economics, Quantitative Marketing, or closely related field.
• Reduced Form Causal Analysis experience.

Job summary
Amazon Hub strives to provide every Amazon customer in every geography a safe, reliable package pickup and return experience conveniently close to where they live or work. Amazon Hub's growing product offering include Lockers, Counters, Campus Lockers, Apartment Lockers, and 3rd-party pickup points etc.

We are looking for a visionary senior economist who is a Reduced Form Causal Analysis expert to join our top-notch cross-domain science team. This position offers an opportunities to apply the frontier of econometrics and economic theory to market design, pricing, forecasting, program evaluation, 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 build Amazon Hub’s foundational causal model for quantifying the holistic economic benefit of the Amazon hub product and service offerings. Your work directly impacts the investment and marketing budget allocation decisions that may touch hundreds of millions of Amazon Hub users and hundreds of millions of packages across Amazon Hub’s worldwide locales. This role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams.

A day in the life
In this role, you will be a technical leader in econometric modeling with significant scope, impact, and high visibility. As the senior economist in the cross-disciplinary 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 analysts 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 Amazon Last Mile organization (which Amazon Hub is part of) 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.

Key job responsibilities

• Build econometrics models to quantify the causal impact of marketing actions and product investment.
• Define and execute an extensive experimental roadmap to test our hypotheses and validate the outputs of our models.
• Provide structure around complex business problems, hone them into specific, scientific questions, and answer them with science, data and reason.
• Advise senior business executives via proper science and analytical mental framework.
• Collaborate with other scientists and data experts on the team to enhance our existing suite of models and get smarter about marketing and product decision-making.
• Mentor junior scientists on real-life application of econometrics methods.

About the team
This role is part of Amazon Hub's central data, analytics and science organization (DAS). The broader DAS team offers additional data expertise in data engineering, business intelligence, data science, operations research and applied science. Plenty of opportunities to cross-pollenate and exercise broader science influence.

• 3+ years of post PhD industry experience. Applicants with considerably more experience, including mid-career, are also strongly encouraged.
• Experience with spatial econometrics.
• 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.