Cyber Threat Intelligence Lead

Cyber Cube delivers the world's leading analytics to quantify digital risk
, helping the largest global carriers, reinsurers and brokers understand, price and manage cyber risk in financial terms.

• AI at our foundation, cyber risk at our core. We don't just use AI, we shape it.

• Built on AI from day one. Artificial intelligence has been part of our strategy since the beginning, blended with deep cybersecurity and insurance expertise and backed by rigorous testing.

• Trusted by more than 100 clients, including 75% of the top 40 European and US cyber insurance carriers and 70% of the top ten reinsurance brokers.

• Backed for global growth. In 2025 Spectrum Equity joined some of Cyber Cube’s financial partners as a new cornerstone investor, accelerating our global growth and fueling innovation across our end-to-end cyber risk analytics for the insurance industry.

• A truly global team across San Francisco, New York, London, and Tallinn.

• A culture of collaboration, openness, intellectual rigor, and ownership for excellence.

• People at the forefront. We encourage Cyber Cubers to challenge themselves, push boundaries, and do the best work of their careers.

• Work in a team of cyber threat analysts, economists, data scientists, actuaries and risk modelers to develop insights, scores, and features for a suite of products delivering cyber risk analytics to the (re) insurance industry

• Own Cyber Cube's point of view on technology risk including factors such as:

  • Offensive capabilities and trends among threat actor classes, and validating Cyber Cube models against observed real-world events,

  • Security hygiene standards (e.g. NIST CSF, CIS) and mitigations for companies to lower their potential likelihood and/or impact of events, and

  • Technology adoption and trends including the adoption, reliance on and governance of artificial intelligence

… translating these factors into the assumptions and scenarios that drive risk models - especially where historical data is limited

• Own the scenario and "event family" library for cyber catastrophe modeling, including emerging AI-driven scenarios

• Own the assumptions register and expert-judgment governance: the documented, client-defensible rationale for modeling choices that are not purely data-driven

• Present Cyber Cube methodology, threat landscape and emerging risk trends to clients and prospects and engage in strategic dialogue with key stakeholders as one of Cyber Cube's key voices and thought leaders on technology risk. Be able to differentiate when speaking with varying technical backgrounds and seniority (e.g. analyst to C-Suite)

• Engage in cross functional collaboration with stakeholders from engineering, product management, analytics personnel, and client facing teams to deliver on projects and product goals

• Deliver various cyber threat intelligence reports - e.g. threat landscape, scenario libraries, changes to mitigation and exploitation assumptions, etc.
  
  - on a quarterly cadence

• Bachelor's or master's degree in cyber security, computer science, statistics, economics, mathematics, or related field

• 3-5 years experience in offensive and/or defensive cyber security (CISSP, CEH, CISM, CompTIA Security+, or other certification preferred)

• Working fluency in Python / R, SQL, flat files and complex data types (JSON, XML), APIs, and Excel - enough to specify and interpret analysis with Data/Analytics teams

• Ability to translate real-world cyber threat behavior into modeling assumptions and scenarios - e.g. scenario likelihoods, severity, and mitigation impacts

• Intellectual curiosity, willingness to learn new skills, and push ideas forward

• Strong critical thinking and problem-solving skills

• Strong communication and consulting presence with key stakeholders

• Experience working in and leading project teams

• Ability to work in an agile, fast-paced startup environment

• Ability to maintain relationships, collaborate effectively, and meet deadlines with a distributed, remote-first workforce

• Ability to think creatively and respond to emerging threats (cyber, AI, other) and their modeling implications in a timely manner

• Experience with analytics and risk modeling

• Experience in a SaaS product development environment

• Familiarity with ML techniques and statistical data analysis

• Familiarity with AI / LLM risk and its implications for cyber risk, social engineering, product safety, errors/omissions, and critical…