PhD Econ Intern, Store Economics and Science

Amazon • Seattle, WA

2d

About The Position

We are looking for detail-oriented, organized, and responsible individuals who
are eager to learn how to apply their causal inference / structural econometrics
skillsets to solve real world problems. The intern will work in the area of
Store Economics and Science (SEAS) and develop models to SEAS.

Our PhD Economist Internship Program offers hands-on experience in applied
economics, supported by mentorship, structured feedback, and professional
development. Interns work on real business and research problems, building
skills that prepare them for full-time economist roles at Amazon and beyond. You
will learn how to build data sets and perform applied econometric analysis
collaborating with economists, scientists, and product managers. These skills
will translate well into writing applied chapters in your dissertation and
provide you with work experience that may help you with placement.

These are full-time positions at 40 hours per week, with compensation being
awarded on an hourly basis.

The Stores Economics and Science Team (SEAS) is a Stores-wide interdisciplinary
team at Amazon with a "peak jumping" mission focused on disruptive innovation.
The team applies science, economics, and engineering expertise to tackle the
business's most critical problems, working to move from local to global optima
across Amazon Stores operations. SEAS builds partnerships with organizations
throughout Amazon Stores to pursue this mission, exploring frontier science
while learning from the experience and perspective of others. Their approach
involves testing solutions first at a small scale, then aligning more broadly to
build scalable solutions that can be implemented across the organization. The
team works backwards from customers using their unique scientific expertise to
add value, takes on long-run and high-risk projects that business teams
typically wouldn't pursue, helps teams with kickstart problems by building
practical prototypes, raises the scientific bar at Amazon, and builds and shares
software that makes Amazon more productive.

Requirements

• Are enrolled in a Ph.D. in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field

Nice To Haves

• Are enrolled in a Ph.D. in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field.
• Candidates should have strong skills in coding in python, machine learning application and causal inference theory

Responsibilities

• Causal inference: The core of the project requires the intern to apply rigorous experimental and quasi-experimental methods (e.g., DiD, matching, IV, or RD) to identify the causal relationship between customer demographic characteristics and upper-funnel shopping behavior. The intern will need to clearly articulate identification assumptions, conduct robustness checks, and demonstrate depth in at least one method — for example, by addressing heterogeneous treatment effects across customer segments or applying modern extensions such as staggered DiD or doubly robust estimation.
• Experiment design: The experiment design deliverable will demonstrate the intern's ability to translate observational findings into a testable hypothesis with a well-specified randomized design, including power analysis, proper randomization strategy, and pre-registration of outcomes.
• Technical adaptability and LLM proficiency: The project requires the intern to quickly learn and leverages LLM-based pipelines. The intern needs an entry-level understanding of large language models and will work hands-on with the most advanced LLM models used internally at Amazon. This demonstrates the intern's ability to operate at the intersection of AI and economics — working independently with large-scale databases using Python and SQL while understanding how LLM outputs feed into economic analysis.
• Communication: The insight report, experiment design, and grocery business proposal will demonstrate the intern's ability to present technical economic ideas clearly to a business audience — translating causal estimates and statistical findings into actionable recommendations that non-technical stakeholders can understand and act on.

Benefits

• Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching.
• Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Education Level: Ph.D. or professional degree