Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 bank, metro location, and mid-level quant role increases applicant density.
Highly specialized credit risk and regulatory modeling limits transferability across industries.
Explicit 4+ years, mandatory quantitative degree, regulatory modeling and technical deployment requirements.
Lead creation, implementation, and documentation of highly complex quantitative models, including market, credit, and operational risk models.
Forecast losses and compute capital requirements using advanced statistical and quantitative methods, influencing global risk assessments and regulatory compliance.
Collaborate with regulators, auditors, and business stakeholders to provide expertise on modeling, analytical strategies, and reporting frameworks related to regulatory credit risk requirements (e.g., CCAR, CECL, IFRS).
4+ years of Quantitative Analytics experience (via work, training, military experience, or education).
Master's degree or higher in quantitative disciplines such as mathematics, statistics, engineering, physics, economics, or computer science.
Experience in Python programming; demonstrated understanding of credit risk modeling and model deployment frameworks.
Experience with implementation/development of regulatory credit risk models (including CCAR, CECL, IFRS), and strong documentation and project management skills.
Advanced programming skills in Python and PySpark with experience in model deployment and monitoring in production environments.
Deep domain expertise in credit risk modeling, regulatory model frameworks, and forecasting methodologies.
Ability to influence cross-functional and global risk assessments by engaging with technical, audit, and regulatory stakeholders.