RISK MODELING SUPERVISOR

Key responsibilities include:
Advanced Scoring Ecosystem:
Lead the development, backtesting, and optimization of full-cycle credit scoring models, including
A-Score
(Application),
B-Score
(Behavior),
C-Score
(Collection),
D-Score
(Drop-off),
F-Score
(Fraud),
IFRS9 ECL model, …
AI/ML Innovation:
Implement Machine Learning algorithms (XGBoost, LightGBM, CatBoost, Neural Networks) to enhance model performance (Gini/AUC) and drive the 'Automation' initiative for instant credit decisions.
AI Agentic Frameworks:
Research and deploy
Agentic AI architectures to automate complex risk reasoning tasks, enabling autonomous AI agents to interact with multiple data sources and internal systems for real-time risk assessment and decision support.
End-to-End Model Governance:
Oversee the entire modeling lifecycle from data gathering, feature engineering, and cleansing to technical documentation, validation, and regulatory compliance.
Strategic Collaboration:
Act as the primary technical liaison for external fintech partners (NICE, Trusting Social, Viettel, VNPT) and internal departments (IT, Data, Policy) to integrate models into live operation flows.
Performance Monitoring & Reporting:
Continuously monitor model stability and portfolio quality using SQL/Python. Provide high-level analytical reports and strategic recommendations to the
Board of Directors (BOD) and
Risk Management Committee (RMC).
Team Mentorship:
Supervise and quality-control the output of Modeling Executives, providing guidance on technical execution and career development.
Coordinate with DIC in AI integration strategies, automation projects of the Company.
Other tasks assigned by the line manager.
JOB REQUIREMENT:
Education:
Bachelor or Master’s degree in Finance, Banking, Economics, Data Science, Data Analytics, MIS, or related fields
Experience:
At least
4-5 years of experience in Credit Risk Modeling or Data Analytics in the banking/consumer finance industry, with at least 1-2 years in a supervisory or team lead role.
AI/ML Mastery (Mandatory):
Proficient in
Python and its libraries (Scikit-learn, etc.) for building advanced predictive models. Deep understanding of Machine Learning frameworks.
Technical Skills
(Mandatory): Expert knowledge of
SQL/Oracle for complex data extraction. Experience with visualization tools (PowerBI/Tableau) and automation (VBA) is a plus.
Digital Mindset:
Deep understanding of the Digital Customer Journey, digital financial products, and Alternative Data.
Regulatory & Risk Knowledge: understanding of SBV Circulars (Circular 39, 18, 14, 27), Basel II/III pillars, and Vietnam's consumer finance landscape is a plus.
Soft Skills:
Excellent leadership and communication skills; ability to translate complex technical concepts into simplified strategic insights for senior management.
Ngành nghề: Kế toán / Kiểm toán, Ngân hàng, Tài chính / Đầu tư
Kinh nghiệm: 4 Năm
Cấp bậc: Trưởng nhóm / Giám sát
Hình thức: Nhân viên chính thức
Địa điểm: Hồ Chí Minh