Description

You will lead the development and validation of probabilistic cyber risk models for insurance and financial services markets.

Responsibilities

• Develop, calibrate, and stress test probabilistic models to quantify the financial impact of cyber risk on single entities and large portfolios.
• Implement methodologies focusing on digital and physical supply chain-related events.
• Build tools to visualize the potential impact of cyber events and integrate modeling processes into production pipelines.
• Define global best practices for data validation, feature selection, and catastrophe exposure modeling.
• Collaborate with Product Management, Engineering, and Client Engagement to communicate technical results to stakeholders.

Required Skills

• 7+ years of experience in statistical data analysis, feature engineering, data visualization, and hypothesis testing.
• PhD or MS in Applied Mathematics, Statistics, Engineering, or a similar quantitative discipline.
• Mastery of deep learning non-parametric models, clustering, anomaly detection, and interpretability.
• Proficiency in Python, R, and SQL.
• Experience with AWS, Databricks, and Apache Airflow.
• Experience working with unstructured, semi-structured, and incomplete datasets.
• Strong technical communication skills for direct client engagement.

Preferred Skills

• Experience in insurance or financial services risk modeling.
• Familiarity with catastrophe exposure modeling frameworks.

Key Skills

Education

Bachelor's degree in Computer Science