トレンド企業

Amazon
Amazon

Work hard. Have fun. Make history.

Economist, Prime Science, Prime Science

職種オペレーション
勤務地Seattle, WA, United States
勤務オンサイト
雇用正社員
掲載3ヶ月前

報酬

$136,000 - $184,000

応募する

福利厚生

健康保険

401k

メンタルヘルスサポート

育児休暇

必須スキル

Economics

R

Python

STATA

Econometrics

Causal inference

Amazon Prime is looking for an ambitious Economist to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), reading, healthcare, and grocery offerings. Prime Science creates insights that power these decisions.

As an economist in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software/data engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the research frontier of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies.

A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep training in one area of econometrics. For example, many applications on the team motivate the use of structural econometrics and machine-learning. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or Py Spark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.

Basic Qualifications

  • PhD in economics or equivalent

Preferred Qualifications

  • 2+ years of industry, consulting, government, or academic research experience
  • Knowledge of at least one statistical software package such as R, Stata, Matlab, SAS
  • Experience in prediction and forecasting in a research or industrial environment
  • Experience with handling of large datasets

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 base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually

閲覧数

0

応募クリック

0

Mock Apply

0

スクラップ

0

Amazonについて

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+

従業員数

Seattle

本社所在地

$1.5T

企業価値

レビュー

10件のレビュー

3.4

10件のレビュー

ワークライフバランス

2.5

報酬

4.2

企業文化

3.0

キャリア

3.8

経営陣

2.7

65%

知人への推奨率

良い点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

改善点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

給与レンジ

4件のデータ

Junior/L3

L2

L6

M3

M4

M5

M6

Intern

L3

L4

L5

Junior/L3 · Warehouse

1件のレポート

$30,509

年収総額

基本給

$23,546

ストック

-

ボーナス

-

$30,509

$30,509

面接レビュー

レビュー6件

難易度

4.0

/ 5

期間

21-35週間

体験

ポジティブ 0%

普通 17%

ネガティブ 83%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge