Job Description

In this role, you'll have an opportunity to use your experience with econometric/statistical modeling, data manipulation, query efficiency techniques, reporting, and automation.


Portfolio Risk Modeling team support and develop regulatory model, execute, and prepare model surveillance along with providing insights for various regulatory requirements. This Role is specific for India Portfolio Risk Modeling team, focusing on Cards CCAR/CECL models. We are currently supporting Champion and owning Benchmark model estimations along with OPMs for all the Cards CCAR /CECL forecasting models. The candidate is critical for project management, timely enhancement and deliverables of benchmark model required for CCAR. The role requires understanding of complex Forecasting Models, prior CCAR knowledge, strong modeling, and analytical skills.


Additionally, you'll build a solid understanding of consumer businesses, functions, systems, data environments, and processes that are necessary for the production and utilization of data.

Responsibilities:

Design, develop, test, and validate statistical models for Cards Portfolio Risk, forecast and model performance monitoring Utilizing graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, panel data analysis, etc. Efficiently design and produce programs to streamline and create repeatable procedures for model development, validation, and reporting Perform deep dive analysis to address ad hoc inquiries on model monitoring, CCAR exercise

Qualifications:

The candidate is expected to have advanced degree (Master's or above) in a quantitative subject, such as Mathematics, Operations Research, Statistics, Economics or Finance and minimum of 9+ years of relevant analytics/modeling experience Proven managerial experience or demonstrated leadership abilities, with a track record of successfully leading and managing quantitative teams Proficiency in Python programming, with experience in the Python/Spark library and operating in CLOUD environment/ ecosystems * Strong communication and presentation skills , with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports