My bulge bracket client is looking for a Quantitative Risk Modeler who will be responsible for building, implementing, and executing statistical models to support impairment, capital and decision model requirements. In this role you will be responsible for building and implementing regulatory models and decision models for acquisition and existing customer management.
Responsibilities:
- Developing predictive models, statistical analyses, optimization procedures, monitoring processes, and score implementations supporting regulatory and decision models
- Driving models through the internal validation process with the validation unit
- Implementing models in Python
- Participating in overall project design and delivery with other functional teams and end-clients
- Producing robust documentation to ensure replicability of results and fulfilling governance requirements
- Providing support for audits of model development and implementation, by both internal and external auditors
Requirements:
- Post graduate university degree in quantitative discipline required
- Extensive knowledge of data analysis, theory and statistical techniques (such as linear or nonlinear models, logistic regression, machine learning, macroeconomic forecast, etc.)
- Experience building regulatory, Impairment (IFRS9/CECL) and decision (acquisition and existing customer management) models for credit cards and unsecured lending
- Broad experience (at least 3 years) with Python, Hive, SAS and SQL programming skills - Python experience preferred
