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Cybercube Jobs (NOW HIRING)

About CyberCube: CyberCube delivers the world's leading analytics to quantify cyber risk , translating one of the most critical risks of today and the future into financial impact for businesses ...

Cybercube information

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$26

$61

How much do cybercube jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for cybercube in the United States is $26.34, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $30.77 per hour, depending on experience, location, and employer.

What does CyberCube do?

CyberCube is a cybersecurity analytics company that provides risk modeling and data analytics solutions for the insurance industry. The role of a CyberCube professional often involves analyzing cyber risk data, developing models, and using tools like Python or SQL to support cybersecurity and risk assessment efforts.

When was CyberCube founded?

CyberCube was founded in 2016 as a cybersecurity analytics company focused on cyber risk modeling for the insurance industry. The company develops tools to help assess and manage cyber risk exposure for insurance professionals and underwriters.

What is the difference between Cybercube vs Cybersecurity Analyst?

AspectCybercubeCybersecurity Analyst
Required CredentialsTypically certifications like CISSP, CISA, or vendor-specific trainingCertifications such as CompTIA Security+, CISSP, or GIAC
Work EnvironmentRisk modeling, data analysis, and cybersecurity simulation platformsMonitoring security systems, incident response, and vulnerability assessment
Employer & Industry UsageUsed mainly by cybersecurity firms, insurance companies, and risk management teamsEmployed across organizations in various industries including finance, healthcare, and tech

Cybercube focuses on cybersecurity risk modeling and data analysis, often within risk management contexts, while Cybersecurity Analysts actively monitor and respond to security threats. Both roles require relevant certifications and work in cybersecurity environments, but their daily tasks and focus areas differ significantly.

What are the key skills and qualifications needed to thrive as a Cybersecurity Analyst, and why are they important?

To thrive as a Cybersecurity Analyst, you need a solid understanding of information security principles, risk assessment, and threat analysis, usually supported by a degree in computer science or related field. Familiarity with industry-standard tools like SIEM systems, firewalls, and certifications such as CISSP or CompTIA Security+ is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help in identifying vulnerabilities and conveying risks to stakeholders. These skills are crucial for proactively defending organizations against evolving cyber threats and ensuring robust data protection.

What jobs can you get in cyber?

In cybersecurity, common jobs include security analyst, penetration tester, security engineer, incident responder, and security architect. These roles involve protecting systems from cyber threats, analyzing vulnerabilities, and implementing security measures, often requiring knowledge of tools like firewalls, intrusion detection systems, and certifications such as CISSP or CompTIA Security+.

What is a CyberCube report?

A CyberCube report is a detailed analysis produced by CyberCube, a risk analytics platform specializing in cyber risk modeling. It provides insights into cyber threat exposure, potential financial impacts, and risk management strategies, often used by insurance companies and cybersecurity professionals to assess and mitigate cyber risks.

What is CyberCube and what does the company do?

CyberCube is a cybersecurity analytics company that provides data-driven solutions for the insurance industry. The company specializes in cyber risk modeling, helping insurers and reinsurers assess and manage cyber risks associated with their clients. CyberCube's platform uses advanced analytics, threat intelligence, and machine learning to evaluate cyber exposures and inform underwriting decisions. Their tools support both single-risk and portfolio-level risk analysis, enabling insurance professionals to better understand and price cyber insurance products.

What are some common challenges CyberCube analysts face when interpreting cyber risk data for insurance clients?

CyberCube analysts often encounter challenges such as navigating large volumes of complex cyber risk data and translating technical findings into actionable insights for insurance clients. Balancing the need for accuracy with tight project deadlines and evolving cyber threats can add pressure to daily responsibilities. Effective collaboration with underwriters, actuaries, and cybersecurity experts is essential, as is staying updated with the latest threat intelligence and regulatory changes. Analysts who thrive in this role typically have strong problem-solving skills and the ability to communicate complex concepts clearly to non-technical stakeholders.
More about Cybercube jobs
Infographic showing various Cybercube job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Physical job distribution, with an average salary of $54,791 per year, or $26.3 per hour.
Lead Cyber Risk & Analytics Engineer

Lead Cyber Risk & Analytics Engineer

CyberCube

New York, NY โ€ข On-site

$130K - $160K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago


Job description

About CyberCube:

CyberCube delivers the world's leading analytics to quantify cyber risk, translating one of the most critical risks of today and the future into financial impact for businesses, markets, and society.

  • 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. Led by investors including Forgepoint Capital, with a $180+ million investment in 2025 from new cornerstone investor Spectrum Equity.

  • 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 CyberCubers to challenge themselves, push boundaries, and do the best work of their careers.

As a key member of the Cyber Risk Modeling (CRM) team, you will research and analyze large, complex cybersecurity datasets to engineer analytical models for the insurance industry.

The CRM team builds cyber risk models that leading insurers and reinsurers rely on for single-risk and portfolio decisions. You will work closely with our Actuarial, Data Science, Data Engineering, and Application Engineering teams to take those models from research into production.

This is a quantitative modeling role with a cyber lens, not a hands-on security job. The cyber side informs the work; the core of the role is translating cyber principles into rigorous statistical models. We want someone quantitative and adaptable who is excited to work at the intersection of modeling, cyber, and insurance.

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. Areas of work include cybersecurity posture, cloud security, malware defense, cyber risk exposure, technology stack dependencies, security practices, and threat actor characteristics.

  • 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.

  • Work closely with the product, analytics, engineering, and client success teams in day-to-day tasks and projects.

  • Look for new and creative ways to bring AI into your work, and share what works with the team.

  • Present models and findings to internal teams, and on occasion to clients, explaining outputs and loss drivers in plain terms.

  • 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.

Skills & Qualifications
  • 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.

  • Eager to work in an agile environment, with the ability to pick up and drop tasks as priorities shift and questions arise.

  • 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.

  • Degree in a quantitative or technical field such as statistics, economics or econometrics, mathematics, data science, or computer science.

Extra Credit
  • Experience with catastrophe or risk quantification models.

  • Awareness of commercial insurance concepts, including cyber insurance, loss ratios, or calculating losses with probabilities and frequencies.

  • 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.

  • Experience at a startup or scaleup.

Our Interview Process

We aim to be transparent and respectful of your time. The process is typically:

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

  • Hiring manager conversation (30 min): the role in depth, the team, and what success looks like.

  • A series of 30-60 minute conversations with team members covering the core areas of the role, including technical depth, communication, and cross-functional collaboration.

Why You'll Love It Here (US)
  • 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

  • Hybrid working, two days a week in the office, plus flexible hours

  • Work abroad for up to three months a year with approval

  • Company-paid learning and development, plus mentorship and secondment programs

  • Dependent care assistance

#LI-Hybrid, #LI-Onsite

AI Fluency at CyberCube

AI is reshaping how work gets done across every function. We value people who are curious about AI, eager to learn, and thoughtful about applying AI tools to work more effectively. AI fluency is part of how we assess every role in our hiring process.

Don't tick every box? Apply anyway.

Research shows the best candidates rarely match a job description point for point. If you're excited about this role and believe you could make an impact, we'd love to hear from you, even if your experience doesn't line up perfectly with everything listed above.

CyberCube Analytics, Inc. is an equal opportunity employer. We do not discriminate on the basis of age, gender, gender identity or expression, gender reassignment, sexual orientation, marital or civil partnership status, pregnancy or maternity, race, color, nationality, ethnicity, religion or belief, disability, veteran status, genetic information, or any other characteristic protected by applicable law.

Compensation Range: $130K - $160K