채용
About the job
Businesses of all shapes and sizes rely on Google’s unparalleled advertising solutions to help them grow in today's dynamic marketing environment. You bring a passion for sales, knowledge of online media, and commitment to maximize customer success. You act like an owner, move with velocity through change, finding innovative and strategic ways to consistently deliver extraordinary and incremental outcomes for both Google and your customers. You build trusted relationships with customers, uncovering their business needs and translating them into powerful solutions to achieve their most ambitious goals. You achieve as a team with sellers, shape the future of advertising in the AI-era, and make a real impact on the millions of companies and billions of users that trust Google with their most important goals.
Google creates products and services that make the world a better place, and g Tech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.
To learn more about gTech, check out our video.
Responsibilities
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Develop an understanding of client marketing and business goals (e.g., Marketing Objective/Client Business Objectives (MOs/CBOs)). Design measurement strategies and define sophisticated Key Performance Indicators (KPIs) tailored to client maturity and eligibility.
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Lead the execution of measurement studies including conversion lift, brand lift, and geo-based experiment. Ensure statistical significance (Stat Sig) on all uplift data.
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Utilize investigative skills to model experimental results and triage them into media plan Return on Investment (ROI) analysis. Analyze attribute lift across channels to inform channel strategy and budget allocation.
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Reconcile data sources (e.g., Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), and Incrementality) to provide a unified narrative of media effectiveness, help clients navigate the shift toward third-party measurement.
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Partner with in-market sales and product specialist teams to interpret measurement results for client leadership.
Minimum qualifications
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Bachelor's degree or equivalent practical experience.
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5 years of experience in marketing analytics, return on investment analysis, and statistical modeling.
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Experience in designing and executing incrementality studies and A/B testing frameworks.
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Experience in managing external and internal stakeholder relationships and owning a portfolio of customers.
Preferred qualifications
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Experience in Media Mix Modeling (MMM), Incremenality and Multi-Touch Attribution (MTA) tools, with the ability to validate and integrate results from multiple measurement sources.
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Experience in SQL, Python, or R for building data models and gathering insights from datasets.
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Experience in defining measurement frameworks for mid-funnel and audience acquisition goals, and moving beyond traditional conversion tracking.
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Knowledge of the technical trends around privacy-safe measurement, conversion analytics, and attribution best practices.
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총 지원 클릭 수
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모의 지원자 수
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스크랩
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Google 소개

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
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