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Verified from career page · Posted 2mo ago

Google

Senior Business Data Scientist, gTech Ads

Google · Google

London

Senior

Machine learning

Last seen 1mo ago

Posted
2mo ago

Posted on 28 July 2026

Workplace
Not specified

Work model not stated

Salary
Not disclosed

Salary range not shared by the company

Visa sponsorship
Not specified

Visa sponsorship details unknown

This role has closed 1mo ago ago. It's kept as a record — see Google's open roles or the similar live roles below.

See Google's open roles

gTech 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.

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.

Develop metrics to track and evaluate solution deployment across teams.

Create dashboards and tools to automate processes, generate reports, and guide product decisions.

Curate and validate data to ensure quality standards are met.

Collaborate with stakeholders to understand the domain, business goals, and data infrastructure context.

Minimum qualifications:

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.

4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

Experience with business or forecasting modeling.

Experience using statistical tools, predictive modeling, or quantitative techniques.

Preferred qualifications:

6 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

About Google

Google runs core product engineering out of London, Dublin, Zurich, Warsaw and Munich — not support functions. Zurich is one of its largest engineering sites anywhere, and Warsaw has grown substantially. The bar is high and the process is long, but these are genuine product teams.

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