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트렌딩 기업

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채용Amazon

Quality Auditor - NL

Amazon

Quality Auditor - NL

Amazon

Den Haag, NLD

·

On-site

·

Full-time

·

1mo ago

필수 스킬

Excel

Machine Learning

We are seeking a detail-oriented Quality Auditor to join our team at AGI-DS. As a Quality Auditor, you will perform systematic quality assessments within our global network of Data Associates, providing manual review and validation of automated quality measurements. This role is critical in maintaining high standards in data quality for AI development and training.

Key job responsibilities
Conduct quality audits on individual workflows and units delivered by Data Associates
Coach and calibrate Data Associates co-located at your site to improve performance
Provide detailed insights on Data Associate-level quality and identify root causes of issues
Perform manual reviews to validate automated quality measurement systems
Document and report quality findings accurately and efficiently
Perform audits to support deep dives and escalations as needed
Maintain strict compliance with quality standards and procedures
Work closely with Quality Audit Managers to improve processes and implement best practices
Contribute to continuous improvement initiatives within the quality assurance team

Basic Qualifications

    • C1+ or equivalent fluency in Dutch language
    • Good working knowledge (B1+) in both spoken and written English
    • Experience in Machine Learning/Data Labeling operations
    • Strong analytical and problem-solving skills
    • Excellent attention to detail Strong communication skills in Business English
    • Experience with quality management tools and systems
    • Ability to work in strict compliance with internal guidelines
    • Understanding of data annotation and quality metrics Proficiency in Excel and data analysis tools
    • Ability to work effectively in a team environment
    • Adaptability to changing priorities and workloads

Preferred Qualifications

    • Prior experience in a quality assurance role within the tech industry
    • Familiarity with AI and machine learning concepts
    • Experience with speech or language data

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Amazon 소개

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+

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