Responsibilities
- Develop, calibrate, validate, and deploy for production 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.
- 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 Computer Science, Applied Mathematics, Statistics, Engineering, or similar quantitative disciplines.
- Mastery in developing and maintaining end-to-end data and modeling pipelines using AWS Glue, Airflow, and Sagemaker.
- Strong programming skills in Python and fluency in data manipulation(SQL, pandas, pyspark) and Machine Learning(Scikit-learn, statsmodel, XGBoost and etc) tools.
- Experience working with AWS (or similar) tools/services like Athena, S3, EC2, Redshift, etc.
- 5+ years of experience in statistical data analysis, feature engineering, predictive modeling, and data visualization
- 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).
- 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.
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