Specialist, Enterprise Risk Modelling
5 hours ago
- PRIMARY OBJECTIVE
- Support the lead in identifying risk modelling & insights use cases for all risk pillars and align to the bank's business objectives
- Support the lead in conducting initial assessment including cost-benefit assessment to prioritise POCs of use cases
- Assist the lead in the setting up of the modelling & insights infrastructure.
KEY RESPONSIBILITIES
Modelling & Insights Capabilities
• Support the lead in the setup and maintenance of the advanced modelling & insights toolkit e.g. strategic set of tools / platforms depending on model type
• Conduct risk modelling & insights on various parts of the portfolio to develop insights for decision making
• Develop forward looking models to assist risk pillars for effective risk management
• Support the lead in the standardisation/automation of core insights to be able to run it on an ongoing basis
• Co-ordinate with Enterprise Risk team to feed the BAU risk insights into reports
• Assist the lead in the development of formal procedure documents governing common activities (e.g. sampling, clustering), common model forms (e.g. regressions, decision trees, hazard models) etc.
Modelling & Insights Infrastructure
• Assist in the setup of data and technology infrastructure to be able to deploy, in a timely manner, best model / approach to perform the task
• Work with Group Analytics CoE to have an easy and timely access to clean and ready data sets
REQUIREMENTS (Qualification/Experience/Skills)
Bachelor Degree Economics, Finance, Math, Statistics, Actuarial Science or equivalent
Preferred level of Experience (by years/function/industry):
• Minimum 6 years of experience in insight and statistical modelling related roles (banking & insurance experience is a plus)
• Proficient in SAS Programming (minimum 5 years) and Proficient Python Programming Language
• Ability to generate modelling & insights to business problems
• Present and communicate with clarity on the modelling & insight solutions
• Work in Agile Environment
• Deep expertise in data mining, insight exploration techniques & solutions
• Hands on experience in handling & managing large quantum of data via appropriate tools & techniques
• Excellent understanding of relevant Big Data tools like SAS, Oracle BDA
• Data Modelling experience (e.g. segmentation)
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