Job Purpose:
The role of the Risk Management division is to continuously anticipate the changing risk profiles of the bank and to take the necessary measures to manage those risks in order to support the business to growth profitably.
The job holder is responsible for end-to-end model development, data governance, data analysis, report & dashboard development & automation, managing model risk management frameworks, and/or supervising interns if assigned.
Key Responsibilities
Model Development. Assist the following based on guidance of supervisor:
- Extract and transform data for model development
- Utilise both traditional statistical models (such as regression) and advanced AI/ML models (such as XGBoost, Neural Networks, etc) to develop models in compliance with regulatory requirements & internal model standards
- Develop models for different purposes: credit risk, fraud risk, pricing, propensity etc.
Data Governance
- Assist Head of Data Science to prepare materials for Data Governance Committee
- Manage data governance activities such as Labeling, Domain Deployment, Data Quality Management etc.
Data Analysis. Perform data analysis in partnership with credit risk & other functional teams
- Extract and transform data for analytics
- Undertake analytics to determine policy effectiveness and efficiency including credit risk, fraud risk, KYC and AML policy
Report Development & Automation. Undertake the following:
- Extract and transform data for reporting
- Utilise MIS tool to automate reporting
Trouble-shoot & implement business rule changes in AML & Fraud Management System:
- Monitor, trouble-shoot, & fix bugs
- Modify or implement new business rules using Power Shell scripts
Job Specification:
University degree/master, preferably in STEM: Data Science, Statistics, Operations Research, Computer Sience, Mathematics, Engineering
- >= 2 years in a bank or a financial institution in data-related roles
- > 2 years in utilising statistical analysis and recommending policies
- > 2 years in MIS/dashboard development: Power BI, Tableau, etc
- > 2 years in Python, R and/or SAS or equivalent
- > 2 years in SQL, or any data querrying application
Technical/Functional skills
- Programming skills such as Python, R and/or SAS, PowerShell
- Business Intellegence tools such as QlikSense, Tableau, SQL
- Datalake/warehouse such as Hadoop/Hive, GCS, BigQuery, AWS
- Banking or consumer finance domain
- Decision rule engines: SAS, FICO, Drools, etc
- Data governance frameworks such as GDPR
Personal skills
- Problem defining & solving
- Stakeholder management
- Project management skills
- Presentation and Communication Skills
