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트렌딩 기업

트렌딩 기업

채용

채용Google

Staff Data Scientist, Research, Search Health

Google

Staff Data Scientist, Research, Search Health

Google

·

On-site

·

Full-time

·

1w ago

  • Research and develop advanced analysis, causal inference analysis of impact, creatve new methodologies (e.g., LLM-based method) to identify product opportunities from various data sources, product headroom analysis for key AI features.

  • Initiate projects inside and across the organization and drive to completion autonomously.

  • Frame and solve ambiguous business problems and communicate the solutions effectively.

  • Interact cross-functionally, be a thought partner and influence a wide range of product stakeholders.

  • Communicate clearly and persuasively and influence product leadership (i.e., VPs and Directors).

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

  • 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.

총 조회수

1

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Google 소개

Google

Google

Public

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

10,001+

직원 수

Mountain View

본사 위치

$1,700B

기업 가치

리뷰

3.7

25개 리뷰

워라밸

3.8

보상

4.2

문화

3.4

커리어

3.9

경영진

2.8

68%

친구에게 추천

장점

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

단점

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

연봉 정보

57,502개 데이터

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0개 리포트

$176,704

총 연봉

기본급

-

주식

-

보너스

-

$150,298

$203,110

면접 경험

9개 면접

난이도

3.4

/ 5

소요 기간

14-28주

합격률

44%

경험

긍정 0%

보통 56%

부정 44%

면접 과정

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense