A senior quantitative developer for Wholesale Credit Risk Loss Forecasting modeling (CCAR/DFAST, CECL).
* Build analytics platform and tools to support / analyze model performance via backtesting, sensitivity and explain, etc, for various applications including CCAR and IFRS9/CECL usages
* Research, develop, and improve the model performance via more advanced statistical methods in machine learning
* Coordinate with other QR teams in model development and analysis.
* Work closely with Tech team delivering the model implementation into production.
Minimum education required:
* Advanced degree in Computer Science, Statistics, or related quantitative field.
Minimum experience required:
* Mathematical modeling and implementation experience in financial industry.
Minimal skills required:
* A 3 to 5 year development experience as a data scientist working on large data projects (data transformation, data analytics, model development, and model validation).
* Strong analytical programming skills (Python, C++) and cross-platform experience with big data (Spark/Hadoop/KDB, etc)
* Good knowledge of financial instruments and financial risk management principles.
* Strong data analysis and statistical modeling skills in factor / correlation models, regression / classification, time series, machine learning and their application in finance
* Ability and motivation to take initiative and solve problems independently
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