Economist II, Selling Partner Growth (amazonjobs)

Job Description

Join us in the evolution of Amazon’s Seller business! The Selling Partner Growth organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential supported by Amazon tools and resources.

We are looking for an Economist II to identify data-driven insight and opportunities to improve our SP growth strategy and drive new seller success. As a successful economist on our talented team of scientists and economists, you will solve complex problems to identify actionable insights, and collaborate with engineering, research, and business teams for future innovation. You need to have solid foundation in econometrics and the ability to connect science with business to address specific business questions. We prefer candidates with strong causal background. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the economic and research community, by working with economists and scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).

Key job responsibilities
As an Economist II in the team, you will:
- Connect economics with business problems and leverage domain expertise to generate data-driven insights and actionable recommendations
- Communicate scientific findings to both technical and non-technical audience to drive for understanding
- Work with our engineering partners to build scientific products
- Involve and contribute to the broader internal & external scientific community

BASIC QUALIFICATIONS

- PhD in economics or equivalent
- 4+ years of industry, consulting, government, or academic research experience
- Experience in causal inference

PREFERRED QUALIFICATIONS

- Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)
- Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
- Experience working with software developers
- Experience in scripting language (e.g., Python)

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $212,800/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.