Deputy Manager Credit Risk
20 hours ago
We are seeking a highly experienced Deputy Manager Credit Risk to join our team in Personal Banking Risk And Integrated Management Department. This full-time role offers an exciting opportunity to apply your risk analytics and modelling expertise in driving strategic decisions across the customer credit lifecycle.
As a Deputy Manager Credit Risk, you will develop predictive models to be deployed in systems, including data analysis, cleaning, sampling, variable selection, modeling, and performance evaluation. You will also conduct regular validation and monitoring on the performance of decision models for retail portfolios and formulate data-driven decision strategies across origination, portfolio management, and collections processes.
Additionally, you will streamline workflows, prepare user requirement documents, and participate in user acceptance tests on decision models. To excel in this role, you should have a strong foundation in mathematics, statistics, or a related field, with at least 2 years of experience in risk analytics or modelling. Proficiency in software like SAS, Python, R, Alteryx, or Tableau is essential, along with hands-on experience in Python, R, or SAS and familiarity with coding standards and best practices.
If you possess a Bachelor's degree in Mathematics, Statistics, Risk Management, Computer Science, Engineering, or Operations Research, and are passionate about applying statistical knowledge, such as segmentation, linear and logistic regressions, machine learning algorithms, and familiar with Generative AI, this might be the ideal opportunity for you. Fluency in English and Mandarin will be advantageous.
Key Responsibilities:
Develop predictive models for system deployment
Conduct regular validation and monitoring on decision model performance
Formulate data-driven strategies across customer credit lifecycle stages
Streamline process and workflow
Prepare user requirement documents and participate in user acceptance tests
Requirements:
Bachelor's degree in Mathematics, Statistics, Risk Management, Computer Science, Engineering, or Operations Research
2 years' experience in risk analytics or modelling
Knowledge of at least one software: SAS, Python, R, Alteryx, Tableau
Hands-on experience in Python, R, or SAS and familiarity with coding standards and best practices
Strong statistical knowledge: Segmentation, Linear and Logistic Regressions, Machine Learning algorithms, Generative AI
Good communication skills and fluency in English and Mandarin
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