Contract
Min 5 Years
Job Description
Looking for Model Validation Quant who can take a critical second line of defense role, ensuring the accuracy, reliability, and regulatory compliance of quantitative models used throughout the firm. This is a highly technical and detail-oriented role for a quant who excels at scrutinizing methodologies and challenging assumptions.
Key Responsibilities
- Validation & Review: Independently perform model validations, annual model reviews, and ongoing monitoring of models used for various purposes (e.g., credit risk, market risk, capital planning).
- Methodology Scrutiny: Conduct a deep dive into the conceptual soundness, mathematical theory, data quality, and assumptions of models to ensure they are fit for purpose.
- Testing & Analysis: Evaluate the models testing approach and results, and perform independent testing, back-testing, and stress-testing to assess reliability under various scenarios.
- Documentation: Document the validation process and results in comprehensive technical reports for stakeholders and regulatory bodies.
- Regulatory Compliance: Ensure all models comply with internal policies, procedures, and external regulatory guidelines (e.g., Basel, Dodd-Frank).
- Communication: Present validation findings clearly and concisely to both technical and non-technical audiences, and provide recommendations for model risk mitigation.
Requirements
- Masters or PhD in a quantitative discipline (e.g., Statistics, Mathematics, Quantitative Finance).
- Strong experience in model validation, model development, or a similar quantitative role within the financial services industry.
- Proficiency in programming languages like Python, R, or SAS for data analysis and testing.
- Excellent understanding of financial instruments, risk management principles, and statistical modeling.
- Meticulous attention to detail and strong analytical, creative thinking, and problem-solving abilities.
- Excellent written and verbal communication skills, with a proven ability to write comprehensive technical reports.
Skills
- Core Technical Skills:
- Programming Languages: Python, R, or SAS are typically required for statistical analysis, data manipulation, and conducting independent tests.
- Statistical and Mathematical Expertise: A deep understanding of statistical theory, econometrics, and stochastic calculus is necessary to scrutinize model methodologies.
- Technical Writing: The ability to document complex quantitative concepts and validation results in clear, concise technical reports.
- Domain-Specific Knowledge:
- Financial Instruments and Risk: A solid grasp of financial products, their underlying models, and various risk types (e.g., credit, market, operational).
- Regulatory Frameworks: Knowledge of relevant regulatory guidelines, such as Basel, is often a requirement.
- Soft Skills:
- Attention to Detail: Meticulous attention to detail is crucial for identifying flaws and weaknesses in models.
- Analytical Thinking: The ability to think critically and challenge assumptions in a constructive manner. <
Experience
Min 5 Years
Preferred
Local / Resident / Eligible to work
Location
Singapore
Mode of Work
On Site
Keywords
Model Validation Analyst, Senior Model Validation Specialist, Quantitative Risk Analyst, Model Risk Quant, Quantitative Analyst, Model Risk Governance & Review