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Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment working with smart & passionate team members.
Our vision is to ensure Amazon Customers have the best experience on Amazon, throughout the year, and do not have to compromise with a less than optimal experience during High traffic / Deal events.
SCOT Team is seeking highly motivated individuals with exceptional data analytics skills and a passion for tackling intricate challenges. In this role, you will utilize your expertise to inform impactful business decisions that enhance customer experience and contribute to long-term free cash flow growth. You will gain a comprehensive understanding of Amazon's systems and supply chain processes through collaboration with diverse teams across product, science, tech, retail categories, finance, and operations.
This role will require partnering closely with Product Managers across SCOT to segment our key Customer Experience and Supply Chain metrics, identify key opportunities to improve our system and process, to deliver Best-At-Amazon experiences for Customers throughout the year.
- Key job responsibilities
- Analyze and synthesize large data streams across multiple systems/inputs.
- Work with Product Managers to understand customer behaviors, spot system defects, and benchmark our ability to serve our customers, improving a wide range of internal products that impact inventory availability for customers both nationally and regionally
- Develop business insights basis data extraction, data analytics, trend deduction & Pattern recognition.
- Present these business insights to senior management/executives.
- Create advanced dashboard to help a large group of teams to consume insights make changes to business process and track progress.
- Build analytical models that can help improve business outcomes at scale enhancing current system abilities.
Basic Qualifications
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
Preferred Qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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.
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1
총 지원 클릭 수
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모의 지원자 수
0
스크랩
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비슷한 채용공고
Amazon 소개

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+
직원 수
Seattle
본사 위치
$1.5T
기업 가치
리뷰
2.9
10개 리뷰
워라밸
2.8
보상
3.7
문화
2.5
커리어
2.3
경영진
2.1
35%
친구에게 추천
장점
Good pay and compensation
Strong benefits package
Flexible scheduling options
단점
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
연봉 정보
4개 데이터
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0개 리포트
$108,330
총 연봉
기본급
$43,332
주식
$54,165
보너스
$10,833
$75,831
$140,829
면접 경험
10개 면접
난이도
3.7
/ 5
소요 기간
21-35주
합격률
20%
경험
긍정 10%
보통 10%
부정 80%
면접 과정
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
뉴스 & 버즈
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