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DART (The Risk Data, Analytics, Reporting & Technology)
We are a diverse group of professionals with backgrounds in physics, engineering, finance, economics, and data science. You will work alongside experienced colleagues to further develop your analytical and quantitative skills. Your responsibilities will include building models and analytical applications to tackle real-world challenges, paving the way for a career as a risk management expert and leader.
Responsibilities:
Research, develop, and test wholesale expected credit loss models in line with IFRS9 or CECL requirements, credit loss models used for regulatory stress testing including CCAR/ICAAP and internal stress testing.
Implement credit loss models in python or other for both model execution, testing, and analytical tools.
Prepare detailed quantitative modeling and analysis for risk managers and senior management.
Synthesize and communicate complex risk models and results.
Conduct statistical analysis, quantitative modeling, and model risk controls.
Work with risk managers, businesses, and tech to design and build models for risk capture and stress testing.
Qualifications:
Master degree from a quantitative field (Mathematics, Physics, Computer Science, Econometrics, Statistics, Economics, Finance, etc.) is required.
2+ years of experience in quantitative financial modeling. Hands-on experience with the research, development, and implementation of financial models.
Ability to apply sophisticated mathematical/analytical techniques to solve real-world problems.
Knowledge of wholesale credit products and financial markets at a financial institution is preferred.
Good knowledge of credit reserves calculation in line with IFRS9/CECL, bank stress testing in line with ICAAP/CCAR or PD/LGD/EAD modeling is a plus.
Familiar with statistics packages and regression models.
Strong programming skills in Python. Good knowledge of Linux is a plus.
Excellent communication skills, verbal as well as written.
We offer:
Time Type:
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