Associate Principal, Quantitative Risk Management
Core
Develop and maintain model performance monitoring within Quantitative Risk Management (QRM), collaborating with quantitative analysts and data staff to implement new analytics and enhance existing tools.
Role type
Associate Principal Quantitative Risk Analyst (Data & Analytics focus)
Builds
Model performance monitoring systems, analytics warehouse data models, and monitoring dashboards
Domain
Financial Services / Quantitative Risk Management
Deliverable
production ML models | dashboards & analysis
Required skills
Python (Pandas, OOP), SQL (complex analytical queries), Git, statistical analysis, financial mathematics, risk management methods, data modeling
Preferred skills
Data orchestration (Airflow), applied statistics, machine learning, numerical methods, Monte Carlo simulation, financial derivatives knowledge, Tableau/Dash, high-performance computing
Technologies
Python, Pandas, SQL, Git, GitHub, Jenkins, Airflow, Tableau, Dash, Alteryx, Confluence, Jira
Responsibilities
Maintain and build data models for analytics warehouse; Perform model performance monitoring implementation and testing; Review implementation of monitoring metrics and algorithms; Write documentation for metrics and prototypes; Develop Python scripts to automate data processing; Conduct visualization and exploratory analysis; Participate in code reviews and troubleshooting
Seniority
Senior, hands-on IC