Data Scientist, Research, gTrade
Data Scientist, Research, gTrade
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Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
- 1 year of experience managing investigative projects.
Preferred qualifications:
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
About the job
Our team is responsible for real-time bidding on behalf of Google Ads advertisers (i.e. GDA and AC). Our optimization modules oversee the transaction of ~20B ARR of ad inventory across web and app display publishers. We optimize bidding across web and app on several exchanges running different types of auctions.
As a Data Scientist, you will solve critical problems for the future of the display ads business. Our work involves data analysis, algorithms design/tuning, data pipelines design/implementation. You will have the opportunity to collaborate within the team as well as with other teams and build knowledge across the display ads ecosystem and the serving stack.
Responsibilities
- Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
- Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
- Own and contribute to the bidding models that govern how Google Ads network bids on real-time auctions for display publisher inventory, across web and mobile properties.
- Improve the product by analyzing auction abuse patterns, duplicate queries, and designing solutions to counter them.
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