Jobs
About the job
g Tech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.
As a Data scientist, you will have the ability to achieve large and tangible impact and the ability to integrate with a large business team and large growing partners. You will be responsible for applying best data science practices to solve our ads customers problems in marketing. You will be passionate about bringing the best of Google’s ML capabilities to build innovative solutions that address our customer's problem-space. You will be responsible for executing on g Tech’s strategy and goals to deliver applied data science to Google's largest ads customers.
The Global Business Organization (GBO) is the engine that powers Google’s full ecosystem of products and services to help customers and partners succeed and grow. GBO includes the commercial arms of Ads sellers, business development teams, and customer services and support, as well as overlay programs that enable coordinated engagement with Google's most complex and important customers and partners.
Responsibilities
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Lead data science aspects of client engagements in the area of marketing portfolio management.
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Collaborate with customers to resolve their problems and identify the best statistical techniques that can solve the problem, and own the development of modeling framework.
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Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a solution.
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Work with customer and internal teams to translate data and model results into tactical and insights for decision-making, and work with clients to integrate recommendations into business processes.
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Collaborate with Product/Engineering teams to increase and optimize capabilities of the Applied DS team, employing methods which create opportunities for scale, and help to drive innovation.
Minimum qualifications
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Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
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3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications
- MBA or Master's degree in a related technical field.
- Experience working with ad tech products, such as ad server, DSPs, DMPs, and web analytics, and an understanding of engineering solutions built for scale.
- Experience working in the ad space, including first-party data onboarding and activation, measurement and data modeling, video and search advertising.
- Ability to communicate in Mandarin and English fluently to support client relationship management in this region.
- Excellent project management, people management and leadership skills, with the ability to formulate data-driven proposals.
- Excellent written and verbal business communication skills.
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About Google

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%
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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
57,502 data points
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
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0 reports
$176,704
total per year
Base
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Stock
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Bonus
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$150,298
$203,110
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
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System Design
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Product Sense
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