Head of Cybersecurity Risk Quantification

Job Title: Head of Cybersecurity Risk Quantification

Location: Warszawa / remote

Job Type: Full-time

Industry: Cybersecurity / Financial Services / Technology

Experience Level: Senior / Executive

About the Role:

We are seeking an experienced and visionary Head of Cybersecurity Risk Quantification to lead our strategic initiatives in measuring and managing cybersecurity risk. In this senior leadership role, you will develop advanced probabilistic risk models, mentor a multidisciplinary team, and drive integration of risk intelligence into enterprise-level decision-making.

Key Responsibilities:

Leadership & Strategy:

• Lead, mentor, and grow a high-performing team of cybersecurity professionals including data scientists, threat hunters, and data engineers.
• Collaborate closely with executive leadership to align risk quantification strategies with overall business objectives.
• Present data-driven risk insights and recommendations to senior stakeholders.
• Serve as a key advisor to regional and business units on emerging cyber threats and their quantifiable impacts.

Risk Quantification & Analytics:

• Supervise the development of Python-based risk modeling tools and libraries.
• Design and implement probabilistic risk assessment models using advanced statistical techniques.
• Build scalable data pipelines using modern cloud-based architectures.
• Integrate diverse data sources (e.g., threat intelligence, financial data, logs) to support comprehensive risk assessments.
• Continuously explore and implement innovative methods in cyber risk quantification.

Required Qualifications:

• Proven leadership experience with a track record of building and developing high-performing technical teams.
• Extensive background in quantitative risk modeling within regulated industries or actuarial science.
• Advanced degree (Master’s or Ph.D. preferred) in a quantitative discipline such as mathematics, physics, statistics, data science, computer science, or engineering.
• Deep experience with probabilistic techniques including Monte Carlo simulations, Bayesian Networks, Markov Decision Processes, decision trees, and structured scenario analysis.
• Experience with Operational Risk modeling, especially in financial services (engineering sector experience also considered).
• Hands-on experience developing decision analysis models and complex numerical solutions in Python.
• Strong statistical and data analysis capabilities.
• Solid understanding of cybersecurity controls and frameworks (e.g., MITRE ATT&CK, threat modeling).
• Experience deploying machine learning models in production environments with knowledge of MLOps best practices.
• Familiarity with data engineering tools such as Spark, Databricks, and Lakehouse architectures.
• Excellent communication and presentation skills with the ability to translate complex risk data into business insights.

What We Offer:

• A dynamic and collaborative work environment.
• Opportunities for continuous professional development and certification.
• The chance to shape the future of cybersecurity risk quantification at an enterprise level.
• Competitive compensation and benefits package.