Minimum 5 years hands on experience in model building methodologies, implementation and compliance. Retail Risk Analytics, Credit Risk Modelling & IFRS9 Expert knowledge of credit scoring techniques, Reporting management & Meeting Deadlines Deep understanding of banking products and credit management concepts and methodologies Ability to construct and maintain complex data structures for comprehensive risk management Degree in Quantitative / Statistics / Actuarial Science / Mathematics (Finance exposure would be a plus); Strong analytical, numerical, research and problem-solving skills Advanced statistical software skills (e.g. SAS EG) Proficient in MS Office, Experience in SQL Experience in open source scripting such as Python/R Experience in working with big data such as Hadoop Ability to present technical concepts for business understanding Team player, self-starter, innovative and highly motivated