Economist, Prime Science, Prime Science
Amazon Science
Seattle, WA3h agovia LinkedIn
This job at a glance
- Who can apply
- New grads, no experience needed
- Must know
- StatisticsProduct managementPythonRData analysis
- Nice to have
- ScalaSQLMachine learningSpark
- Work
- On-site in Seattle
- Pay
- Not stated by the employer.
- Skill demand
- Statistics31%Python20%Product management6%of 99 similar entry-level jobs posted in the US this week
- Listed
- Oct 28, 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
Amazon Prime is seeking an ambitious Economist to generate econometric insights for worldwide Prime. This role is central to major company decisions impacting Amazon's customers across diverse industries such as e-commerce shipping, digital content (streaming video, music, gaming, photos), reading, healthcare, and grocery. Prime Science develops insights that drive these decisions.
Key Responsibilities
- Create statistical tools that embed causal interpretations.
- Utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, experimentation), and machine-learning.
- Publish scientific findings in internal or external journals and conferences.
- Collaborate closely with economists, applied scientists, data professionals, product managers, and software/data engineers.
- Generate insights from descriptive statistics and novel statistical/econometric models.
- Develop automated scientific data products for internal Amazon use to inform company decisions.
- Write strategic documents advising senior company leaders on utilizing insights for sustainable customer value.
Requirements & Tech Stack
- Demonstrated capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, machine-learning) using software such as R, Python, or STATA.
- Willingness to learn and apply a broad set of statistical and computational techniques.
- Strong writing and emotional intelligence skills for collaborative teamwork.
- Growth mindset.
- Capacity for dealing with a high level of ambiguity.
A plus would be knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark.
Qualifications
- PhD in economics or equivalent.
- Knowledge of data analysis languages (e.g., R, Stata, Python, etc.) or other statistical software.
- Experience with SQL.
- Track record of delivering projects well and on-time, preferably in collaboration.