Business Data Scientist, Trust and Safety, YouTube
Summary
A Business Data Scientist on YouTube's Trust and Safety team frames ambiguous abuse/safety problems into quantitative analyses, builds and scales metrics, analysis frameworks, and AI-based systems, and communicates recommendations to executives. Core tools are Python, R, SQL, statistics, and AI/Generative AI pipelines, working cross-functionally with Data Science, Product, Research, and Strategy.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.
Fast-paced, dynamic, and proactive, YouTube’s Trust and Safety team is dedicated to making YouTube a safe place for users, viewers, and content creators around the world to create, and express themselves. Whether understanding and solving their online content concerns, navigating within global legal frameworks, or writing and enforcing worldwide policy, the Trust and Safety team is on the frontlines of enhancing the YouTube experience, building internet safety, and protecting free speech in our ever-evolving digital world.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Develop, build, and measure performance on YouTube-wide abuse performance metrics and operational metrics (productivity, efficiency, timeliness, etc.), and generate insights to improve the business's ability to decrease the prevalence of violative content on the platform.
- Lead the design, implementation, and scaling of metrics, analysis frameworks, and AI-based systems, creating standardized and defensible solutions applicable across products and violation areas.
- Learn complex and technical concepts and systems and deliver meaningful results using them. Communicate highly technical results and methods clearly.
- Partner with Data Science, Product, Research, and Strategy teams to prioritize and execute sophisticated quantitative analyses and advanced modeling that deliver actionable insights.
- Analyze processes to identify opportunities for improvement, define requirements, and collaborate cross-functionally and globally to improve processes and tools as AI-Native.
Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Preferred qualifications:
- 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
- Experience architecting scalable enterprise AI solutions and Generative AI pipelines.
- Experience in project management and process optimization with AI or data analytics.
- Familiar with abuse prevention, policy and regulatory systems.
- Proven ability to proactively take ownership of projects by setting and achieving milestones, synthesizing input from many stakeholders, managing multiple projects simultaneously, creating outputs appropriate to the audience(s) and driving final deliverables.
- Excellent written and verbal communication skills.