Head of Risk Analytics, Modeling and Model Validation Center – ID10409

1. Strategic Leadership & Governance
Define and execute VPBank's risk analytics, modeling and model validation strategy in alignment with the Bank's strategic priorities, AI-enabled risk transformation agenda and Basel roadmap.
Establish and maintain the Group Model Risk Management Framework, model governance standards, model inventory, tiering and lifecycle requirements.
Represent RMD in model governance committees and engagements with SBV, auditors and other relevant stakeholders.
Ensure alignment of modeling, validation and risk analytics capabilities across VPBank and subsidiaries, with clear ownership and accountability.
Outcomes/Measures: regulatory compliance; effective execution of the transformation roadmap; positive audit and regulatory assessments; model risk maintained within approved tolerance.
2. Oversight of Model Development Department
Provide strategic direction for the development, enhancement, implementation and monitoring of risk, regulatory and business models across VPBank Group.
Oversee credit risk models, including application, behavioral, collection, attrition, cross-sell, propensity and early-warning models; Basel II/III/IV, IFRS 9, stress testing, capital and portfolio analytics models; and advanced AI/ML, fraud analytics and alternative-data models.
Establish modern development methodologies, coding and documentation standards, reusable assets and common feature libraries.
Drive industrialized model development and deployment through MLOps, automated pipelines, CI/CD, controlled retraining and performance monitoring, in coordination with Business, IT and EDA.
Outcomes/Measures: delivery against model roadmap; improved Gini/KS and model stability; shorter development and deployment cycle time; increased proportion of models deployed and monitored through automated pipelines.
3. Oversight of Model Validation Department
Ensure independent, risk-based and timely validation of all material models across VPBank Group in accordance with the Model Validation Framework.
Approve the annual validation plan and oversee validation of credit, market, liquidity, operational, regulatory and business models.
Establish validation standards for AI/ML models, including explainability, stability, data integrity, bias and fairness where applicable, implementation accuracy and ongoing monitoring.
Ensure effective challenge of model methodology, assumptions, data, implementation and performance; track findings and remediation to closure.
Embed model-risk controls into MLOps, including end-to-end lineage, versioning, dev-to-production consistency, tiered change control, retraining guardrails and continuous evidence for audit and review.
Outcomes/Measures: percentage of validations delivered on schedule; timely closure of findings; validation quality; critical model coverage; no material overdue validations.
4. Oversight of Risk Strategy & Analytics Department
Lead the Risk Strategy & Analytics function as VPBank's Risk Analytics Center of Excellence, while managing RMD's strategic initiatives and transformation portfolio.
Establish common analytics standards, methodologies, playbooks, performance dashboards and value-tracking mechanisms across Risk and the Group.
Coordinate Basel, risk data, digitalization, EWS, fraud analytics, collections analytics and other cross-divisional transformation initiatives.
Develop portfolio analytics and forward-looking risk insights to strengthen underwriting, pricing, limits, monitoring, collections and executive decision-making.
Lead the Risk Analytics capability roadmap and Risk Academy, including technical training, on-the-job coaching, knowledge transfer and internal certification.
Outcomes/Measures: strategic initiatives delivered on time and to quality; measurable value realization; increased analytics maturity; completion of capability-building and knowledge-transfer milestones.
5. Research, Innovation & Continuous Improvement
Lead research and controlled adoption of emerging AI, machine learning, GenAI and Agentic AI applications in risk management.
Sponsor innovation pilots in underwriting, fraud detection, collections, early warning and portfolio monitoring, with appropriate human oversight and governance.
Promote automation across model development, validation, deployment, monitoring, documentation and reporting.
Benchmark VPBank's risk analytics and model risk management capabilities against international standards and leading financial institutions.
Outcomes/Measures: innovative use cases transferred into production; increased automation; improved time-to-market and model quality; demonstrable risk or business impact.
6. People Leadership & Organizational Development
Build and lead a high-performing team of model developers, validators, risk strategists and analytics professionals across the three departments.
Define workforce and succession plans, assign KPIs, evaluate performance, and coach technical and leadership talent.
Foster a culture of analytical rigor, independence, innovation, collaboration, continuous learning and accountability.
Outcomes/Measures: employee engagement and retention; succession readiness; improved technical capability; completion of development and certification plans.
1. Educational Qualifications
Master's degree or higher in Statistics, Mathematics, Quantitative Finance, Economics, Data Science, Computer Science or a related discipline
Professional certification such as FRM, CFA, PRM, PMP or an equivalent qualification is preferred.
2. Relevant Knowledge/ Expertise
Deep expertise in credit risk modeling, independent validation and model risk management.
Strong knowledge of Basel II/III, IRB, IFRS 9, stress testing, capital adequacy and portfolio analytics.
Strong understanding of AI/ML governance, explainability, model monitoring, risk data architecture and MLOps.
Knowledge of advanced analytics applications in early warning, fraud, collections and credit decisioning; familiarity with modern analytics platforms and alternative data.
3. Skills
Strong strategic leadership, stakeholder management and influencing skills.
Advanced quantitative, analytical, problem-solving and executive communication skills.
Strong transformation and project portfolio management capability.
Working knowledge of SAS, SQL, Python or R, modern data platforms, model deployment and system integration.
4. Relevant Experience
At least 12 years of relevant experience in banking risk management, analytics, model development or model validation, including at least 5 years in a senior leadership role.
Proven experience leading large-scale risk analytics, model risk or data/technology transformation programs.
Demonstrated experience engaging regulators, auditors, executive management and cross-functional stakeholders.
5. Required Competencies
Strategic thinking and vision alignment.
Leadership, talent development and succession building.
Analytical rigor, sound judgment and decision-making.
Independence, integrity and professional ethics.
Innovation mindset, collaboration and continuous improvement orientation.
Benefits
Competitive salary and bonus package
Staff loan with special interest rates
Training courses based on the job, Training framework/Learning RoadMap for each position
Insurance in accordance with Labor laws + VPBank Care insurance for all employees. (insurance covered for family members for entitled employees);
Annual leave (varied based on job grade)
Travel allowance
A dynamic and friendly working environment, full of great opportunities to develop your career and abundant interesting activities to join (Sports competitions, talent contests, teambuilding…)
Working time: from Monday to Friday & 2 Saturday mornings/month.
Ngành nghề: Ngân hàng, Tài chính / Đầu tư, CNTT - Phần mềm
Kinh nghiệm: 12 Năm
Cấp bậc: Quản lý
Hình thức: Nhân viên chính thức
Địa điểm: Hà Nội