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Google

Research Data Scientist, YouTube Ads Bidding

Google

Published 14 May 2026
Mountain View, CA, USA
147K - 211K USD Annual
Full Time
27500 - 275000 people

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Role Highlights

Languages used

Python
SQL

Key skills

Data Infrastructure
Machine Learning
Data Science
Operations Research
Statistical Analysis
Statistics
Mathematics
Physics
Economics
Quantitative
PhD
Optimization
Modelling

Tools, Libraries and Frameworks

Mountain View
ADS

Description

The role involves building reliable and scalable offline and serving infrastructure for YouTube ads bidding. The individual will focus on innovating new direct response products and identifying sources of poor performance. The position requires solving complex bidding optimization problems through a mixture of engineering, machine learning, and analytical work. The professional will define standard metrics and models to be used in bidding processes. Additionally, the role entails collaborating with stakeholders to translate business questions into tractable analysis and mathematical models.

Required Qualifications and Skills

Candidates must possess a Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. A minimum of 3 years of work experience using analytics to solve product or business problems, coding, or querying databases is required, or a PhD degree. The role necessitates effective investigative skills and strong statistical modeling capabilities. Proficiency in English is required for all roles.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

Google

Size

275773

Website

goo.gle

HQ

Mountain View, US

Public/Private

Public Company

Description

At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.

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