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Quantitative Threat Forecasting Analyst

OpenAI

$320,000 - $425,000
Jun 10, 2025
San Francisco, CA, US
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The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem.

Requirements

  • Expertise with modern toolchains—NumPyro, TensorFlow Probability, PyMC, Darts, GluonTS/Chronos, sktime, PyOD 2.0, River, scikit‑survival—and readiness to evaluate emerging libraries as the field evolves.
  • Strong coding skills (Python/JAX/PyTorch or R) and data‑engineering fundamentals (SQL, Spark, data warehousing).
  • Deep fluency in statistical inference, forecasting, uncertainty quantification, and decision modeling—especially under sparse or adversarial data conditions.

Responsibilities

  • Design probabilistic & Bayesian models using PyMC, NumPyro (JAX‑accelerated HMC/NUTS) and TensorFlow Probability to capture uncertainty at scale.
  • Build classical and deep‑learning forecasts with statsmodels baselines, plus state‑of‑the‑art libraries like Darts, GluonTS, Chronos, sktime and Nixtla’s MLForecast for multivariate or long‑horizon time‑series problems.
  • Develop real‑time anomaly‑detection pipelines leveraging PyOD 2.0 for GPU‑ready detectors and River for streaming/online ML on telemetry data.
  • Apply survival‑analysis and rare‑event methods (e.g., Cox PH, random‑survival‑forests, DeepSurv) via scikit‑survival to model threat lifecycles and hazard rates.
  • Run stress tests & Monte Carlo simulations to evaluate the likelihood and impact of low‑frequency, high‑severity threats; translate findings into resilient safety‑engineering requirements.
  • Own production pipelines in Python/JAX/PyTorch or R, using SQL or Spark‑like engines (DuckDB, BigQuery, Snowflake) and GPU/TPU acceleration where appropriate.

Other

  • 5+ years experience in a quantitative research, forecasting, or risk modeling role in finance, tech, safety, security, or public policy
  • Crisp communicator able to influence multidisciplinary partners and executives.
  • Comfort navigating imperfect data and prioritizing under uncertainty in a rapidly changing threat landscape.