[Hiring] Senior Data Scientist @Empirical Security

Role Description

Empirical Security is seeking an experienced Security Data Scientist focused on building the next generation of cybersecurity vulnerability models. Our unique approach leverages ground-truth telemetry to develop predictive, actionable insights that transform the way organizations identify, prioritize, and remediate vulnerabilities in cloud, appsec, and traditional environments. We build models specific to individual customers, and maintain many of them side by side.

You own models and data end to end: problem framing, features, training, evaluation, deployment, and the uncomfortable part where you explain to a customer why the vulnerability their board is worried about ranked 400th on the remediation list.

What you'll do

• Design, train, and ship exploit prediction models against ground-truth exploitation telemetry, in cloud, appsec, and traditional infrastructure.
• Build evaluation that survives contact with reality: precision, recall, coverage, efficiency, calibration, and how all four decay over time.
• Solve for extreme class imbalance, acknowledging that a fraction of a percent of published CVEs are ever exploited in the wild.
• Work the hard part of the dual-model architecture: partial pooling, hierarchical priors, and cold-start behavior for customers whose local telemetry is thin in month one and rich in month twelve.
• Engineer features across scanner output, EDR, asset inventory, identity, cloud posture, and exploitation telemetry, and be honest about which ones are leakage.
• Own monitoring and drift detection.
• Publish papers, methodology write-ups, open benchmarks, and conference talks.
• Partner with engineering and our forward deployed team to move models out of notebooks and into production systems that customers depend on.

Qualifications

• Several years of applied machine learning or statistics with models that ran in production and had consequences when they were wrong.
• Fluency in Python and SQL, with discipline in version control, reproducible pipelines, and secure handling of customer data.
• Real depth in classification under heavy imbalance, plus at least one of: survival and time-to-event analysis, Bayesian hierarchical modeling, or causal inference.
• Calibration instincts; discomfort when a model outputs 0.9 and is right 60% of the time.
• The ability to explain a model to a security executive and quantify uncertainty out loud.
• Curiosity about attacker behavior to ask why a feature works, not just whether it does.

A Final Word

Don't check off every box in the requirements listed above? Please apply anyway! Studies have shown that marginalized communities - such as women, LGBTQ+ and people of color - are less likely to apply to jobs unless they meet every single qualification. Empirical Security is dedicated to building an inclusive, diverse, equitable, and accessible workplace that fosters a sense of belonging – so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to still consider submitting an application. You may be just the right candidate for this role or another one of our openings!