Lead Data Scientist, Cyber Catastrophe Risk Model

Responsibilities

• Develop, calibrate, validate, and stress test probabilistic cyber risk models for the (re)insurance and financial services markets.
• Develop and implement methodologies to quantify the financial impact of cyber risk on single entities as well as large insured portfolios, with a specific focus on digital/physical supply chain-related events.
• Develop and implement tools to effectively visualize the potential impact of cyber events.
• Explore different data sources to come up with features and assumptions to enhance our set of probabilistic risk models.
• Integrating/automating modeling processes in our production pipeline to feed our platform.
• Define and implement a globally consistent best practice process for data validation, feature selection, and modeling of catastrophe exposures.
• Champion best practices to design and extend a rapid and flexible modeling framework.
• Communicate results to internal and external stakeholders.
• Engage and collaborate directly with clients on a deep technical level.
• Collaborate with other leaders across the Analytics organization, including Product Management, Engineering, and Client Engagement.

Qualifications and Requirements

• PhD or MS degree in Applied Mathematics, Statistics, Engineering, or similar quantitative disciplines.
• Mastery of deep learning non-parametric models, clustering, anomaly detection, and interpretability.
• 5+ years of experience in statistical data analysis, feature engineering, data visualization, and hypotheses testing.
• True passion for leading, inspiring, mentoring, and attracting world-class colleagues.
• Experience working with different types of datasets (e.g., unstructured, semi-structured, with missing information).
• Proficiency in Python or R, and SQL.
• Experience working with tools such as AWS Athena, Databricks, Apache Airflow, etc.
• Excellent written and verbal communication skills.
• Ability to think critically and creatively in a dynamic environment, while picking up new tools and domain knowledge along the way.
• A positive attitude and a growth mindset.