Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity.

The Sr. Economist, Kuiper Marketing, will lead the development of state-of-the-art, scalable models to measure the effectiveness and efficiency of marketing. In this critical role, you will leverage your deep expertise in causal inference to design and implement robust measurement frameworks that provide actionable insights to drive strategic business decisions.

The right person in this role will be able to deal with ambiguity and take the lead in defining frameworks where no prior examples exist. They will be an ambitious self-starter with ability to operate independently and thrive in a fast-paced environment. Demonstrated ability and willingness to roll up sleeves and execute to get the job done will be key to success in the role. The successful candidate will have:
- Experience applying causal inference and marketing science techniques, such as econometrics, machine learning, and randomized experiments.
- Proven track record of developing and implementing sophisticated, scalable models to measure marketing effectiveness and attribution.
- Expertise in programming languages (e.g., R, Python) and proficiency in working with large, complex datasets.
- Strong problem-solving skills, ability to think critically, and a keen eye for detail.
- Excellent communication and presentation skills, with the ability to translate technical analyses into actionable business insights.
- Experience in a fast-paced, data-driven environment, with the flexibility to adapt to changing business needs.

Key job responsibilities
- Collaborate cross-functionally with marketing and commercial teams to define the measurement strategy and ensure alignment on objectives.
- Leverage large, complex datasets to uncover hidden patterns and trends, extracting meaningful insights that inform marketing optimization and investment decisions.
- Develop advanced econometric and machine learning models to rigorously evaluate the causal incremental impact of marketing campaigns on customer perceptions and behaviors.
- Work with engineers and data scientists to automate models in a production environment.
- Stay up-to-date with the latest research and methodological advancements in causal inference and machine learning to continuously enhance the team's capabilities.
- Effectively communicate analysis findings, recommendations, and their business implications to key stakeholders, including senior leadership.
- Mentor and guide scientists and engineers fostering a culture of analytical excellence and innovation.

Export Control Requirement:
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

BASIC QUALIFICATIONS

- PhD in economics or equivalent
- Experience in econometrics (e.g., program evaluation, forecasting, time series, panel data, or high dimensional problems), economic theory, and quantitative methods
- Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)
- Experience in building statistical models using R, Python, STATA, or a related software
- Experience in analytics and applied economics
- Experience with marketing measurement and decision science

PREFERRED QUALIFICATIONS

- Experience in developing and executing an analytic vision to solve business-relevant problems
- Experience in industry, consulting, government or academic research
- Experience productionizing science models and deploying them to scale

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.