# Data Scientist, Preparedness

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA, California
**Role:** Data Science
**Salary:** $347k – $400k/yr
**Skills:** Python, SQL, Data Science, Machine Learning, Classifiers, Experimentation, Causal Inference, Dashboards, Monitoring, Cybersecurity
**Posted:** 2026-02-26

> Data Scientist evaluates and improves AI mitigation systems, focusing on classifiers and detection pipelines for risks like biosecurity and cybersecurity. Builds monitoring frameworks and drives cross-functional impact using Python, SQL, and analytical expertise.

## Job Description

## What You’ll Do
- Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., **biosecurity**, **cybersecurity**, emerging risk areas).
- Diagnose false positives and false negatives with deep error analysis, root cause investigation, and clear recommendations.
- Build monitoring and measurement frameworks to track mitigation effectiveness over time and across user segments/use cases.
- Identify trends in over-blocking vs. under-blocking, quantify customer impact, and propose prioritized interventions.
- Develop insights from customer feedback, complaints, and usage patterns to detect shifts in adversarial behavior and system failure modes.
- Expand risk monitoring into new areas, including cybersecurity threats and model loss-of-control/sabotage scenarios, partnering with domain experts.
- Communicate results to technical/executive stakeholders with crisp narratives, decision-ready metrics, and clear tradeoffs.

## Qualifications
- Significant experience in **data science** or applied analytics in high-stakes domains (e.g., security, trust & safety, abuse prevention, fraud, platform integrity, reliability).
- Strong foundations in experimentation, causal thinking, observational inference; design robust measurement under imperfect data.
- Fluency in **SQL** and **Python** (or equivalent) for analysis, modeling, monitoring workflows.
- Experience building metrics, dashboards, operational monitoring that changes outcomes.
- Track record driving cross-functional impact with engineering, product, research partners.

**Nice-to-haves:**
- Cybersecurity data science experience (threat modeling, adversarial dynamics, abuse patterns, security telemetry).
- Classifier evaluation, calibration, thresholding, error analysis at scale; familiarity with detection systems in adversarial settings.
- Trust & Safety experience.
- Interest in AI safety, alignment, catastrophic risk prevention.

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