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Strategy and Insights Manager, Large Customer Sales (English, Mandarin)

Google

Strategy and Insights Manager, Large Customer Sales (English, Mandarin)

Google

placeShanghai, China; Beijing, China; +2 more; +1 more

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Uncapped earning potential

Team trips

Base salary plus commission

Stock options

Equity

Required Skills

HubSpot

Salesforce

LinkedIn Sales Navigator

About the job

Google's Large Customer Sales (LCS) teams are strategic partners and industry thought leaders to the world's leading brands and agencies. We continuously challenge how customers think about their business and how Google can support growth. We focus on helping these players navigate profound industry shifts and drive outsized business performance by competitively selling Google's full suite of advertising solutions across Search, YouTube, Measurement, and more. As a member of our LCS team, you'll have the unique opportunity to sell at the forefront of technology, collaborating with executives, influencing market-shaping strategies, and delivering tangible results that significantly impact major global businesses and drive the growth of Google.

Responsibilities

  • Provide support and consulting on client's/partner’s strategy in the areas of sales, marketing and product development, and translate data into answers to business questions and insights to facilitate business decision-making.

  • Develop analytical modeling for key client/partner projects, apply and customize analytical tools (e.g., dashboards) and frameworks to identify opportunities, and develop solutions to enhance client/partner business and improve the use of Google products.

  • Collaborate with sales teams to drive business growth with clients/partners, conduct analysis and identify business opportunities, and support the development of go-to-market business pitch and marketing collateral.

  • Build and manage relationships with client/partner stakeholders across functions and levels, and own the relationship with the data/analytical stakeholders on the client’s/partner’s side.

Minimum qualifications

  • Bachelor's degree or equivalent practical experience.

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

  • Ability to communicate in English and Mandarin fluently to support client relationship management.

Preferred qualifications

  • 1 year of experience with marketing measurement and attribution techniques (e.g., offline measurement, MMM, MTA, attribution) and Google advertising products (e.g., Google Ads, Google Analytics, Google Marketing Platform, etc).

  • 1 year of client-facing experience, and ability to influence across levels.

  • Knowledge of SQL, databases, and automation techniques (e.g., dashboards, automating custom reports, tables).

  • Ability to analyze datasets and distill them into insights.

  • Excellent communication skills with the ability to deliver stories to audiences of all levels.

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About Google

Google

Google

Public

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

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

3.7

25 reviews

Work Life Balance

3.8

Compensation

4.2

Culture

3.4

Career

3.9

Management

2.8

68%

Recommend to a Friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

Cons

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

Salary Ranges

63,375 data points

Junior/L3

Mid/L4

Junior/L3 · Account Manager

955 reports

$235,140

total / year

Base

$138,750

Stock

$55,227

Bonus

$41,164

$148,728

$383,799

Interview Experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer Rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview Process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense