Specialist, Enterprise Risk Modelling & Insights

PRIMARY OBJECTIVESupport the lead in identifying risk modelling & insights use cases for all risk pillars and align to the bank’s business objectivesSupport the lead in conducting initial assessment including cost-benefit assessment to prioritise POCs of use casesAssist the lead in the setting up of the modelling & insights infrastructure.Key ResponsibilitiesModelling & 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 setsREQUIREMENTS (Qualification/Experience/Skills)Bachelor Degree Economics, Finance, Math, Statistics, Actuarial Science or equivalentPreferred 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)Other Skills Required 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)