Cyber Risk Quantification Product Lead

Mastercard; Beşiktaş; On-site; TRY 900,000 - 1,300,000; Full time

Job summary

Mastercard is seeking a Cyber Risk Quantification Product Manager to lead quantitative risk analysis and FAIR-based modeling within our cybersecurity products group. The role emphasizes translating cyber risk concepts into actionable product requirements and clear business explanations, collaborating across product, analytics, and engineering teams.

The ideal candidate combines hands-on risk modeling experience with strong problem-solving skills, governance, and a practical approach to

Qualifications

• 5+ years hands-on experience in cyber risk quantification or related analytics.
• Practical experience applying FAIR-based methodologies to risk scenarios or products.
• Experience building, calibrating, validating, or explaining quantitative models.
• Strong governance, validation, documentation, and explainability of quantitative models.
• Solid grounding in statistics, probability, and financial impact estimation.

Responsibilities

• Support development, calibration, validation, and explanation of FAIR-based cyber risk models.
• Translate methodologies into clear product requirements and user-facing explanations.
• Apply concepts of exposure, control and financial impact to practical use cases.
• Collaborate with product, engineering, analytics, cybersecurity, and risk teams to refine requirements.
• Maintain documentation that explains model workings, assumptions, and outputs.

Skills

Cyber risk quantification

Quantitative risk assessment

FAIR methodologies

Model calibration

Model validation

ROI analysis

Job description

Mastercard is seeking a Cyber Risk Quantification Product Manager to lead quantitative risk analysis and FAIR-based modeling within our cybersecurity products group. The role emphasizes translating cyber risk concepts into actionable product requirements and clear business explanations, collaborating across product, analytics, and engineering teams.

The ideal candidate combines hands-on risk modeling experience with strong problem-solving skills, governance, and a practical approach to