Cybcube

Cybcube

Lead Cyber Risk & Analytics Engineer

New York Office

Sponsorship not specifiedDetected 23 days ago
PythonSQLData EngineeringData ScienceData VisualizationStatisticsCybersecurityCRMLogisticsResearchCommunicationCollaborationMentoringAdaptabilityActuarial ScienceRisk Modeling

About the role

  • We don't just use AI, we shape it. - Built on AI from day one.
  • We encourage CyberCubers to challenge themselves, push boundaries, and do the best work of their careers.
  • You will work closely with our Actuarial, Data Science, Data Engineering, and Application Engineering teams to take those models from research into production.

Responsibilities

  • Build, validate, and refine defensible analytical cyber risk models for single-risk and aggregate risk products in the insurance industry.
  • Refine and build technographic models that integrate cybersecurity, insurance, and risk modeling through research and large datasets, bringing in new technologies, data sources, and techniques to make the models more valuable and representative.
  • Translate cyber principles and large, complex datasets (including threat intelligence) into model inputs and financial measures: frequencies, severities, probabilities, and the trends that drive loss over time.
  • Contribute robust internal and external documentation in the form of model documents, industry studies, informational videos, and code comments.
  • Support cyber catastrophe model clients through change management, and channel their questions and feedback to the Product & Analytics team to shape future model direction.

Requirements

  • You have built or worked on predictive or statistical models, whether in econometrics, statistics, or internal business modeling, and worked with large datasets.
  • Eager to work in an agile environment, with the ability to pick up and drop tasks as priorities shift and questions arise.
  • You have read and written Python and a query language such as SQL, enough to follow and interpret code in a live setting.
  • You know when it genuinely helps and when it does not, you can get useful results from it, you check its output against the source, and you stand behind whatever you produce with it.
  • Degree in a quantitative or technical field such as statistics, economics or econometrics, mathematics, data science, or computer science.
  • Experience with catastrophe or risk quantification models.
  • Graduate degree in a related quantitative or engineering discipline such as mathematics, actuarial science, statistics, data engineering or computer science.
  • Familiarity with database schemas and queries in SQL or NoSQL.
  • Experience with data visualization in Tableau, Python, R, or Excel.
  • Experience working in an agile team.
  • Self-starter able to work well in independent and various team settings, including with teammates in other time zones.
  • Intellectual curiosity with willingness to learn new skills and contribute ideas.
  • Demonstrated quantitative modeling experience. You have built or worked on predictive or statistical models, whether in econometrics, statistics, or internal business modeling, and worked with large datasets.
  • Strong written and verbal communication, including summarizing technical analysis for decision makers who are not technical, using dashboards, charts, or tools like Tableau.
  • A genuine interest in cybersecurity. Early-stage knowledge is fine; curiosity and aptitude matter more than years of practice.
  • Programming literacy. You have read and written Python and a query language such as SQL, enough to follow and interpret code in a live setting. You do not need to be an expert developer.
  • Sound judgment about working with AI. You know when it genuinely helps and when it does not, you can get useful results from it, you check its output against the source, and you stand behind whatever you produce with it.
  • Awareness of commercial insurance concepts, including cyber insurance, loss ratios, or calculating losses with probabilities and frequencies.

Nice to have

  • your background, motivation, and the role, plus logistics and compensation.
  • Recruiter screen (30 min): your background, motivation, and the role, plus logistics and compensation.

Compensation

  • Competitive salary, 4% 401(k) match, and unlimited PTO

Benefits

  • Led by investors including Forgepoint Capital, with a $180+ million investment in 2025 from new cornerstone investor Spectrum Equity.
  • Competitive salary, 4% 401(k) match, and unlimited PTO
  • Premium health coverage (medical, dental, vision) with CyberCube covering your full deductible
  • Generous paid parental leave
  • Company-paid learning and development, plus mentorship and secondment programs
  • Hybrid working, two days a week in the office, plus flexible hours

Company info

  • Artificial intelligence has been part of our strategy since the beginning, blended with deep cybersecurity and insurance expertise and backed by rigorous testing.
  • A truly global team across San Francisco, New York, London, and Tallinn.
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This listing is sourced directly from Cybcube's careers page and normalized into a canonical job model.