Job Purpose
- General: Responsible for leveraging internal and external data to provide insights and information related to big data, machine learning, optimization methods, and statistical rule/model building which supports a facts-based decision making process to operational risk management strategies và policies.
- Specialization: Responsible for portfolio/risk types that being assigned to manage.
Key Accountabilities (1)
- Analyze data to identify potential risks, track controls/ mitigations effectiveness, assess risks, monitor risks, investigate root cause of risk events and establish additional controls.
- Algorithm and qualitative model: Measure risks and automate risk response decision through both statistic and expert adjustment, Qualitative scorecard to assess risk.
- Build and monitor bank wide operational risk limits, allocate operational risk limits according to the Bank's key business areas and operational risk subtypes.
- Develop data analytics report and dashboard through data visualization.
Key Accountabilities (2)
- Manage and control operational risk status of the bank operational risk portfolio; build and maintain data information system for an effective operational risk management
- Calculate operational risks according to Basel II, national legislation and internal models.
- Perform other related tasks at the request of the Director of Operational Risk Management, Senior manager of Data analytics and Portfolio Management
Key Accountabilities (3)
Key Relationships - Direct Manager
Key Relationships - Direct Reports
N/A
Key Relationships - Internal Stakeholders
Business Units/Supporting Units/Internal Auditing/Units with unit control function in the bank
Key Relationships - External Stakeholders
Inspectors/External Audit
Success Profile - Qualification and Experiences
Experience
- At least 6 years of relevant work experience and at least 02 years of people management experience.
- Having in-depth knowledge and experience in banking operations and operational risk management.
- Quantitative and analytical skills in risk modeling
- Experience with other programming and data manipulation languages (SAS/SQL, C/C++, Java, big data tools...) and other systems rules engine experience
- Proficiency with stastistical programs such as R or Python is an advantage.
Qualifications
- Having a university degree or higher in relevant economic/ data analysis/ statistic
- TOEIC: 550-649
