채용
Benefits & Perks
•Parental leave
•401(k) matching
•Generous paid time off and holidays
•Professional development budget
•Comprehensive health, dental, and vision insurance
•Parental Leave
•Learning
•Healthcare
Required Skills
JavaScript
React
PostgreSQL
Quality Specialists play a vital role in establishing and maintaining comprehensive quality frameworks across our operations.
- Key job responsibilities
- Define and implement quality metrics for established workflows
- Create prescriptive actions for quality issues
- Partner with customers, operations and internal support teams to optimize workflow quality
- Conduct side-by-sides to identify opportunities for workflow enhancement and quality improvements
- Analyze data trends and develop solutions
- Monitor quality performance and coach operations teams
- Create and maintain quality metrics reports
- Handle customer escalations and recommendations
- Evaluate and suggest improvements for quality tools
- Support process documentation and implementation
A day in the life
Quality Specialist's primary responsibility begins with developing robust quality strategies in collaboration with customers and CPMs, encompassing metrics, audit approaches, and specific targets for each workflow. When quality issues arise, these specialists create prescriptive actions, examining data patterns to formulate effective solutions. They maintain a continuous improvement cycle by managing a critical feedback loop between operations and customers, drawing insights from multiple sources including quality auditors, side-by-side observations, and metric analysis. Through regular side-by-side sessions, they identify opportunities for workflow enhancement and quality improvements. The specialists serve as key escalation points for customer concerns, providing strategic recommendations based on their deep understanding of processes. They consistently evaluate quality tools, suggesting refinements to enhance effectiveness, while simultaneously maintaining and updating process documentation to ensure standardization and clarity across all workflows. This comprehensive approach ensures quality remains at the forefront of our operational excellence.
Basic Qualifications
- Bachelor's degree or equivalent
- C1+ CEFR English language proficiency, both written and spoken
- C1+ CEFR Arabic language proficiency, both written and spoken
- Intermediate Excel skills (VLOOKUPS, PIVOTS, formulas)
- Experience in Machine Learning/Data Labeling
- Strong process expertise in data services
- Experience in coaching and process improvement
- Analytical and problem-solving capabilities
Preferred Qualifications
- Experience with speech or language data preferred
- Ability to work in ambiguous environments
- Project management experience
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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About Amazon

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+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
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 reports
$181,968
total / year
Base
-
Stock
-
Bonus
-
$154,672
$209,264
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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