Model Risk & Validation Lead

Tonik; Pasig; Sur place; PHP 1 200 000 - 1 800 000; Plein temps

Résumé du poste

Tonik in the Philippines seeks an experienced Model Risk Validator to fortify the second line of defense. You will review and validate quantitative models, ensure data quality, and monitor validation coverage across business units.

You will prepare model-risk reports for governance, support regulatory examinations, and train stakeholders on validation expectations. A strong grounding in statistics, ML, and banking risk disciplines is essential.

Qualifications

• Bachelor's degree in a quantitative field; postgraduate degree is an advantage.
• 5+ years of experience in banking, financial services, fintech, model validation or risk analytics.
• Experience reviewing or challenging statistical, financial, risk, or ML models.
• Knowledge of banking risk disciplines (credit risk, expected credit loss, liquidity, etc.).
• Proficiency in SQL and at least one analytical language (Python, R, SAS, MATLAB).

Responsabilités

• Perform independent validation of models across the bank's units, covering conceptual soundness and data quality.
• Develop and maintain a risk-based validation plan prioritizing materiality and regulatory significance.
• Prepare periodic model-risk reporting for governance bodies and the Board.
• Escalate material model-risk concerns to CRO and committees.
• Support regulatory examinations, Internal and External Audits related to model risk.

Connaissances

Statistical modeling

Machine learning

Communication skills

Independence

Formation

Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Computer Science, Engineering, Actuarial Science, Finance, Accounting, or another relevant quantitative discipline

Outils

SQL

Python

R

SAS

MATLAB

Description du poste

Tonik in the Philippines seeks an experienced Model Risk Validator to fortify the second line of defense. You will review and validate quantitative models, ensure data quality, and monitor validation coverage across business units.

You will prepare model-risk reports for governance, support regulatory examinations, and train stakeholders on validation expectations. A strong grounding in statistics, ML, and banking risk disciplines is essential.