採用

Intern - Economics, Measurement Intelligence Science Team (MIST)
New York, NY, USA
·
On-site
·
Internship
·
2w ago
We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference skillsets to solve real world problems. The intern will work in the area of Amazon Ads measurement and incrementality and develop models to quantify bias between observational and causal conversion path rate metrics.
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.
Key job responsibilities
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.
Basic Qualifications
- Knowledge of SQL or Python
- Currently enrolled in an advanced year of a Ph.D. program in Economics, specializing in applied microeconomics with a focus on reduced-form causal inference.
Preferred Qualifications
- Experience in applied economic analysis with big data, causal inference, machine learning and data science
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, NY, Astoria - 142,100.00 - 192,200.00 USD annually
USA, NY, New York - 142,100.00 - 192,200.00 USD annually
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Amazonについて

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
従業員数
Seattle
本社所在地
$1.5T
企業価値
レビュー
2.9
10件のレビュー
ワークライフバランス
2.8
報酬
3.7
企業文化
2.5
キャリア
2.3
経営陣
2.1
35%
友人に勧める
良い点
Good pay and compensation
Strong benefits package
Flexible scheduling options
改善点
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
給与レンジ
4件のデータ
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件のレポート
$181,968
年収総額
基本給
-
ストック
-
ボーナス
-
$154,672
$209,264
面接体験
10件の面接
難易度
3.7
/ 5
期間
21-35週間
内定率
20%
体験
ポジティブ 10%
普通 10%
ネガティブ 80%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
ニュース&話題
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