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Amazon
Amazon

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Economist, Prime Science, Prime Science

职能运营
地点Seattle, WA, United States
方式现场办公
类型全职
发布3个月前

薪酬

$136,000 - $184,000

立即申请

福利待遇

医疗保险

401k

心理健康支持

育儿假

必备技能

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

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关于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+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

10条评价

3.4

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.0

职业发展

3.8

管理层

2.7

65%

推荐率

优点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

缺点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

薪资范围

4个数据点

Junior/L3

L2

L6

M3

M4

M5

M6

Intern

L3

L4

L5

Junior/L3 · Warehouse

1份报告

$30,509

年薪总额

基本工资

$23,546

股票

-

奖金

-

$30,509

$30,509

面试评价

6条评价

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 17%

负面 83%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge