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The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. Our team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability The Integrity pillar within Applied Foundations is responsible for the scaled systems that help identify and respond to bad actors and harm on OpenAI’s platforms. As the systems that address some of our most severe usage harms become more mature, we’re adding data scientists to help us measure robustly the prevalence of these problems and the quality of our response to them.
Job Responsibility
own measurement and quantitative analysis for a group of severe, actor- and network-based usage harm verticals
develop and implement AI-first methods for prevalence measurement and other productionised safety metrics, which may necessarily include off-platform indicators or other non-standard datasets
build metrics that can be used for goaling or A/B tests when prevalence or other top line metrics are not suitable
own dashboards and metrics reporting for harm verticals
conduct analyses and generate insights that inform improvements to review, detection, or enforcement, and that influence roadmaps
optimise LLM prompts for the purpose of measurement
collaborate w/ other safety teams to understand key safety concerns and create relevant policies that will support safety needs
provide metrics for leadership and external reporting
develop automation to scale yourself, leveraging our agentic products
Requirements
are a senior DS with trust and safety experience that can drive measurement direction
have deep statistics skills, specifically around sampling methods and prevalence estimation of complicated problem areas (ideally activity- rather than content-based)
have experience working with severe and sensitive harm areas like child safety or violence
are an excellent communicator, and have strong cross-functional collaboration skills
are capable in data programming languages (R or python, SQL)
(ideally) have experience with AI harms or leveraging AI for measurement
Nice to have
have experience with AI harms or leveraging AI for measurement