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职位Google

Staff Product Data Scientist, Workspace Collaboration Data Science

Google

Staff Product Data Scientist, Workspace Collaboration Data Science

Google

·

On-site

·

Full-time

·

1w ago

  • Define, own and evolve product success metrics. Report, analyze and forecast trends of key product metrics and make recommendations to improve them.

  • Lead the design, analysis, and interpretation of product experiments. Proactively perform data exploration to understand user behavior and identify opportunities for improving and growing Workspace products.

  • Apply technical expertise with observational data analysis, modeling, and causal inference to answer the most important product questions.

  • Partner with Product, Engineering, UX and cross-functional teams to influence, prioritize and support product strategy.

  • Deliver effective presentations of data-driven insights and recommendations to multiple levels of stakeholders.

  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

  • 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree.

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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