My client is looking to fill a VP level role in which you will be developing robust and cutting-edge agile modeling solutions solutions to meet business needs in the areas of loss forecasting, ALLL, stress testing and capital planning. Candidates should have 5+ years of relevant experience including proficiency in regulatory modeling frameworks models (preferably Credit Cards or Consumer Lending) along with statistical/quantitative and software/programing skills using big data (Python, Pyspark).
Responsibilities:
- Develop agile modeling solutions to meet business needs in the areas of loss forecasting, ALLL, stress testing and capital planning by applying appropriate methodologies - including, but not limited to, regression, forecasting, clustering, decision trees, simulation, optimization, and machine learning using Python/PySpark and big data environment
- Support the development of automated, standardized and scalable modeling solutions across data mining, segmentation, regression, back testing, reporting and ongoing monitoring components to speed up model development process
- Perform "what-if" analysis with regards to change in market conditions, change in regulations or changes in the strategy, to guide business decisions for risk and revenue optimization
- Provide thought leadership on decision science methodology and development processes and provide insights and reporting on portfolio performance
- Provide leadership and guidance to junior modelers for their technical and professional development
Requirements:
- Bachelor's degree in quantitative field and 5+ years of Consumer Lending statistical modeling / analytics experience
- Familiarity with model development and governance standards across the banking sector, especially as related to credit card and consumer lending
- Strong statistical/quantitative and software/programing skills using big data (Python, Pyspark)
- 3+ years managing a team and providing thought leadership to support model development activities
