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

Expert, Operational Risk Management