Product Data Scientist, Geo Abuse and Risk
Description For Product Data Scientist, Geo Abuse and Risk
Google is seeking a Product Data Scientist for their Geo Data Insights and Analytics (GDIA) Abuse and Risk team. This role combines advanced statistical analysis with modern AI techniques to protect Google Maps from bad actors while ensuring a positive contributor experience. The position involves working with large-scale data sets, developing complex sampling algorithms, and utilizing Large Language Models for content moderation. As part of Google's engineering-driven culture, you'll collaborate with Engineering, Operations, and Product teams to drive meaningful improvements in data moderation performance. The role offers the opportunity to impact Google's billion-plus user base through data-driven decision making and strategic insights. The ideal candidate will blend strong quantitative skills with excellent communication abilities to translate complex analyses into actionable business recommendations. This position represents a unique opportunity to work at the intersection of data science, machine learning, and trust & safety, while contributing to one of Google's core products.
Responsibilities For Product Data Scientist, Geo Abuse and Risk
- Perform large-scale data analysis, statistical modeling and inferential ML to identify opportunities for improvement and measure the impact of initiatives
- Work on complex sampling algorithm development to model rare events and use stochastic methods in understanding the real-world impacting our data moderation performance
- Use tools such as Gen AI and similarity based clustering to remove bad content or help develop mitigation mechanisms
- Work with large data sets, build robust data pipelines, automate data extraction, and build monitoring/reporting dashboards for leadership
- Prioritize and communicate user needs, make recommendations and drive implementation for product or process changes
Requirements For Product Data Scientist, Geo Abuse and Risk
- Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience
- 3 years of experience with statistical data analysis, data mining, and querying (e.g., SQL)
- 1 year of experience managing analytical projects
