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Data Solutions Lead, Data Collection Excellence

职能数据科学
级别Lead级
地点Den Haag, Netherlands
方式现场办公
类型全职
发布3个月前
立即申请

福利待遇

医疗保险

401k

股权

通勤补贴

必备技能

Customer communication

ML data operations

Data annotation

Technical consultation

As a Data Solutions Lead, you'll be the trusted advisor for our AGI-DS scientists, providing expert consultation on ML/Gen AI data collections and managing customer relationships. You'll drive business value through technical advisory and partnership building, creating and managing workstreams that delight our customers and deliver meaningful change for the models that back them.

Key job responsibilities
Drive and document effective ML/GenAI solutions for customer requests, transforming complex research objectives into clear, actionable data collection requirements
Coordinate across teams to ensure seamless delivery and stakeholder alignment
Own relationships with customer scientists, becoming their go-to partner for ML data solutions
Provide consultation on ML workflow capabilities, helping customers maximize value
Monitor and optimize collection health metrics to ensure customer success
Drive customer adoption through providing technical value and the provision of an exemplary customer experience.

You'll also:
Guide customers on workflow feasibility and data collection best practices
Collaborate with implementation teams to define and validate technical requirements
Evaluate scalability of annotation scenarios and provide strategic recommendations
Influence technical documentation and guidelines

Basic Qualifications

  • Bachelor's degree in a relevant field or equivalent work experience
  • Demonstrated experience in effectively defining optimal data creation strategies and executing them
  • 2+ years of experience in ML data operations, with a strong understanding of data annotation/ML workflows and concepts
  • Outstanding customer communication and management skills, especially in technical consultation
  • Ability to translate complex technical concepts into tactical applications

Preferred Qualifications

  • Bachelor's degree in Computer Science, Business or a related field
  • Experience in project management
  • Working knowledge of JSON, Command Line, and Python
  • Technical account management experience
  • Background in customer success or solution consulting

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.

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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

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

Junior/L3 · Data Scientist L4

0份报告

$181,968

年薪总额

基本工资

-

股票

-

奖金

-

$154,672

$209,264

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