Data Scientist focused on safety at OpenAI, building analytics to measure harmful behavior, detect fraud, evaluate safety systems, and inform critical decisions on AI deployment. Requires strong SQL/Python, statistical reasoning, and experience with causal analysis.
230k – 325k/yr
HybridData Science
About the role
Responsibilities
Measure harmful or abusive behavior across OpenAI’s products
Detect fraud, manipulation, and coordinated misuse
Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows
Design experiments and causal analyses to understand product, policy, and mitigation impacts
Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks
Diagnose gaps in safety and integrity systems using behavioral and product data
Quantify and navigate false positive / false negative tradeoffs
Translate ambiguous safety risks into measurable problems and evidence-based recommendations
Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes
Build zero-to-one analytical systems in rapidly evolving domains
Requirements
Strong statistical reasoning and analytical judgment
Experience with experimentation, causal inference, or observational analysis
Strong SQL and Python skills
Experience working with messy, incomplete, or noisy datasets
Ability to structure open-ended business or risk problems
Excellent communication with technical and non-technical stakeholders
High ownership and comfort operating independently
Nice-to-Haves
Background in Trust & Safety / Integrity
Experience with Fraud & abuse
Security analytics experience
AI/ML model measurement and evaluation
Alignment and AI safety research
Background in Biosecurity, synthetic biology, infectious diseases, or computational biology
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