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CyberCube is seeking a Lead Actuary to apply statistical methods and stress-test internal models for comprehensive insurance analytics. You will collaborate with cross-functional teams to interpret key findings and communicate results to stakeholders.
You will validate models, adapt to a changing environment, and participate in internal R&D while providing analytical support to teammates in a fast-paced, global setting.
CyberCube 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 CyberCube’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.
People at the forefront. We encourage CyberCubers to challenge themselves, push boundaries, and do the best work of their careers.
We are looking for a Lead Actuary to apply statistical methods for comprehensive analysis, stress-test internal models, collaborate on interpreting key findings, and communicate results to internal and external stakeholders.
Identify, evaluate and recommend statistical methods for use in analysis as appropriate
Stress-test internal models on an ongoing basis to ensure output meets expectation and customer demand, while helping find bugs or corner cases that need attention
Identify, interpret and validate key findings with team members to ensure high-quality deliverables
Communicate analysis results effectively with internal and external customers
Continuously validate and adapt model to changing environment
Participate in internal research and development activities, as needed
Provide analytical/actuarial support to other team members, as needed
Search and identify relevant sources of publicly available information/data that will support the development and enhancement of new and existing underwriting and actuarial tools
Review each data source carefully to ensure consistency, identify deficiencies and perform basic tests/analysis to confirm accuracy and improve quality of the data
Create comprehensive documentation for the different modules involved in the creation of internal tools.
Organization, Attention to Detail, Confidentiality, Thoroughness, Independence, Ability to Analyze Information, Results Driven, Bias Toward Efficiency
Ability to work independently and in a team environment
Excellent analytical and problem-solving skills
Hands-on experience with VBA, SQL, R, Python, Tableau or other statistical software
Bachelor’s degree in a related quantitative discipline such as statistics, actuarial or data science, economics, mathematics and/or relevant work experience
3 to 5 years of relevant work experience
Play an instrumental role in reshaping one of the key industries in the world
Generous healthcare benefits with dental and vision coverage
Flexible working hours and the option to work from home when necessary
Opportunity to participate in a secondment program
Company supported mentorship program
Grow in a collaborative, respectful, and empathetic culture
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.
CyberCube Analytics, Inc. and CyberCube Analytics Europe Limited is an equal opportunity employer. We don’t tolerate discrimination against age, gender, gender identity, gender expression, sexual orientation, race, color, nationality, ethnicity, religion, disability, veteran status, protected genetic information or political affiliation.