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职位Google

Data Transformation Lead, Education and Careers

Google

Data Transformation Lead, Education and Careers

Google

·

On-site

·

Full-time

·

1w ago

  • Develop and advocate for AI-driven marketing strategies, creating a compelling vision for how Google's solutions address client challenges and unlock growth. Influence executive stakeholders to adopt these strategies, demonstrating a deep understanding of their business and their propensity to adopt new AI solutions.

  • Lead clients in modernizing their data infrastructure for advanced AI, establishing best practices and a long-term data strategy. This involves assessing data maturity, designing technical implementation plans, and ensuring secure platform integration.

  • Act as a key technical advisor, translating complex concepts into clear stories for business stakeholders. Drive the delivery and activation of AI solutions, collaborating with partners, and ensuring alignment with client's goals.

  • Partner with sales and product teams to identify opportunities and drive growth.

  • Bachelor's degree or equivalent practical experience.

  • 8 years of experience in media analytics, advertising sales, digital media and marketing, consulting, or financial analysis.

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关于Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

员工数

Mountain View

总部位置

$1,700B

企业估值

评价

3.7

25条评价

工作生活平衡

3.8

薪酬

4.2

企业文化

3.4

职业发展

3.9

管理层

2.8

68%

推荐给朋友

优点

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

缺点

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

薪资范围

57,502个数据点

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0份报告

$176,704

年薪总额

基本工资

-

股票

-

奖金

-

$150,298

$203,110

面试经验

9次面试

难度

3.4

/ 5

时长

14-28周

录用率

44%

体验

正面 0%

中性 56%

负面 44%

面试流程

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense