Model Risk Management Specialist

Ryt Bank; Kuala Lumpur; On-site; MYR 180,000 - 280,000; Full time

Job summary

Ryt Bank is seeking a Model Risk Management Specialist to join the 2LoD team. The role focuses on validating traditional and AI/ML models, ensuring conceptual soundness, regulatory compliance, and ethical governance.

Responsibilities include independent technical validation, data lineage review, documentation, and reporting to the CRO and Risk Management Committee. The candidate should have strong quantitative expertise and excellent communication skills for executive audiences.

Qualifications

• Master’s or PhD in Statistics, Mathematics, Financial Engineering, Data Science, CS, or Econometrics.
• 5+ years in model validation, quantitative risk management, or advanced data science in banking or financial services.
• Ability to translate complex models into understandable risk insights.

Responsibilities

• Conduct independent technical validations of high‑risk models (credit risk, market risk, etc.).
• Assess AI/ML algorithms, data lineage, hyperparameters, and training methodology.
• Maintain and update the model inventory; document methodology and findings per standards.
• Provide validation summaries to CRO, Risk Committee, and model owners; escalate material issues.
• Ensure compliance with BN Malaysia frameworks and global regulatory expectations.

Skills

Model validation

Statistical analysis

Communication

Regulatory knowledge

Explainability

Education

Master’s degree or PhD in quantitative field

Tools

Python

R

SQL

SAS

TensorFlow

PyTorch

Job description

The **Model Risk Management (MRM) Specialist** operates within the Second Line of Defence (2LoD) to manage, validate, and mitigate risks arising from the bank's mathematical, statistical, and Artificial Intelligence (AI/ML) models. This role focuses on ensuring that traditional quantitative models (e.g., credit risk, stress testing) and advanced AI systems (e.g., Generative AI, LLMs, machine learning credit scoring) are conceptually sound, compliant with regulations, and governed ethically.This position reports directly to the **Chief Risk Officer**.**Key Responsibilities****Model Validation & Conceptual Review*** **Technical Validation:** Conduct independent technical validations of high-risk models, including credit risk models, Expected Credit Loss (MFRS9) models , market risk, AML transaction monitoring, and financial forecasting systems.* **AI & Machine Learning Assessment:** Review and challenge advanced AI algorithms, including deep learning, NLP, and Generative AI models. Assess data lineage, hyperparameter tuning, and training methodology.* **Explainability & Bias Mitigation:** Evaluate AI models for explainability (XAI), interpretability, algorithmic bias, data drift, and ethical implications. Ensure models do not produce discriminatory outcomes.**Governance, Inventory & Documentation*** **Model Inventory Control:** Maintain and update the comprehensive Bank-Wide Model Inventory, ensuring all traditional and AI/ML models are properly tiered by risk level.* **Documentation Standards:** Produce comprehensive validation reports documenting methodology, findings, and recommendations in line with the Bank's validation standards; present findings to the model development team and escalate material issues to CRO and RMC, BRMC; Assist in preparing model risk governance materials for the Risk Management Committee, including validation summaries and model risk status updates* **Performance Monitoring:** Establish metrics to monitor ongoing model performance, data drift, and model decay, triggering re-validation or remediation when thresholds are breached.* Support the model risk governance process by tracking open findings and action plans, following up with model owners on remediation timelines, and flagging overdue items.**Regulatory Compliance & Strategic Risk*** **Framework Alignment:** Ensure the bank’s model inventory complies with global and regional regulatory expectations, including **Bank Negara Malaysia (BNM) frameworks** (e.g., Credit Risk, Risk Governance Policy Documents), **MFRS**, and emerging **AI Governance Frameworks**.* **Effective Challenge:** Deliver an independent, constructive, and rigorous \"effective challenge\" to data scientists, quantitative developers, and First Line (1LoD) business owners regarding model limitations and risks.* **Committee Reporting:** Prepare clear validation reports and synthesize complex technical vulnerabilities into executive summaries for the Risk Committee (MRC) and Chief Risk Officer (CRO).**Required Skills & Qualifications****Education & Experience*** **Education:** Master’s degree or PhD in a highly quantitative field such as Statistics, Mathematics, Financial Engineering, Data Science, Computer Science, or Econometrics.* **Experience:** **>5 years of experience** in model validation, quantitative risk management, or advanced data science within a banking, financial institution, or financial consulting environment.**Technical & Core Competencies*** **Programming Proficiency:** Advanced hands-on coding skills in **Python, R, SQL, or SAS** for data manipulation and statistical replication.* **AI/ML Frameworks:** Practical familiarity with machine learning libraries and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) and automated validation tools.* **Banking Domain Knowledge:** Deep comprehension of financial products, risk metrics (PD, LGD, EAD), stress testing methodologies, and economic capital modeling.* **Communication:** Ability to articulate complex mathematical and algorithmic concepts clearly to non-technical business stakeholders and senior executivesJR00000653