Risk modeling senior executive

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 3 years of experience in Credit Risk Modeling or Data Analytics in the banking/consumer finance industry

• 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: 3 Năm

Cấp bậc: Trưởng nhóm / Giám sát

Hình thức: Nhân viên chính thức

Địa điểm: Hồ Chí Minh