Description

Job Description

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.
7+ 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.

Education

Bachelor's degree in Computer Science