Quantitative Cyber Risk Researcher — Attack Surface Signals

CyberCube; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

CyberCube is seeking a Quantitative Cyber Risk Engineer to translate internet engineering and cyber risk concepts into measurable signals. You will work with data scientists, engineers, and product teams to quantify exposure and inform risk models for the cyber insurance industry.

You’ll design novel signals based on network configurations, asset footprints, and Internet-scale data, contributing to next‑gen analytical engines in a global company.

Qualifications

• Deep understanding of internet fundamentals and core protocols (TCP/IP, BGP, DNS, HTTP/S, TLS).
• Strong ability to design quantitative metrics and scoring logic for risk exposure.
• Able to translate complex network concepts into measurable data signals.
• Bachelor’s or Master’s degree in CS/Engineering/Math/Statistics or related field.
• 3–5+ years in network engineering, cyber threat research, or risk modeling.

Responsibilities

• Design rigorous risk signals from network architecture and internet footprint.
• Translate theoretical concepts into empirical, actionable risk metrics.
• Perform architectural deep-dives into internet-facing protocols and cloud infra.
• Research emerging cyber threats and map them to asset configurations.
• Collaborate with product, analytics, and engineering to productionize risk signals.

Skills

Deep Internet & Networking

Strong Quantitative Acumen

Analytical Mindset

Educational Background

Experience

Education

Bachelor’s or Master’s degree in a highly quantitative/technical field

Tools

Python

SQL

Spark

Job description

CyberCube is seeking a Quantitative Cyber Risk Engineer to translate internet engineering and cyber risk concepts into measurable signals. You will work with data scientists, engineers, and product teams to quantify exposure and inform risk models for the cyber insurance industry.

You’ll design novel signals based on network configurations, asset footprints, and Internet-scale data, contributing to next‑gen analytical engines in a global company.