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PhD Econ Intern, Store Economics and Science

Amazon

PhD Econ Intern, Store Economics and Science

Amazon

Seattle, WA, USA

·

On-site

·

Internship

·

1w ago

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.

About the team
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.

Basic Qualifications

  • In your 3rd year or greater of a PhD program in Economics or other quantitative field

Preferred Qualifications

  • Experience in Statistical Analysis packages such as R, SAS and Matlab

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.

The starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location. 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.

USA, WA, SEATTLE - 129,200.00 - 174,700.00 USD annually
USA, WA, Seattle - 129,200.00 - 174,700.00 USD annually

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

$1.5T

Valuation

Reviews

2.9

10 reviews

Work-life balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

4 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0 reports

$181,968

total per year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

Interview experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge