Model Risk Validation

TopNotch HR Consulting Firm; Kuala Selangor; On-site; MYR 60,000 - 80,000; Full time

Job summary

A leading consulting firm in Kuala Selangor is seeking a Model Validation Analyst to manage end-to-end validation of models in line with regulatory requirements. The role demands strong quantitative skills and proficiency in programming languages like Python, SQL, or R. Candidates should have at least 2 years of experience in quantitative modelling, with a solid understanding of credit modelling and data science techniques. Collaboration with various stakeholders is essential to propose risk mitigation strategies and enhance model risk management frameworks.

Qualifications

• At least 2 years / 5+ years of work experience in quantitative modelling.
• Familiar with modern and emerging technology techniques.
• Interest to stay abreast of industry developments.

Responsibilities

• Perform independent model validation for new/existing models.
• Collaborate with stakeholders for model risk identification.
• Validate IFRS9/Basel models including PD, LGD, EAD.

Skills

Passionate in Data

Credit modelling

Data science techniques

Coding (Python/SQL/R)

Quantitative problem solving

Education

Advanced degree in quantitative discipline

Tools

Python

SQL

R

Job description

TopNotch HR Consulting Firm – Kuala Selangor, Selangor

Perform independent model validation as part of the second line of defence, drive the effective implementation of the Model Risk policy and recommend improvements.

1. Manage and complete the model validation from end to end for new/ existing models in the bank, which covers:

a. Qualitative review: underlying model assumptions and algorithms, i.e. supervised learning and unsupervised learning models, use of model & its interpretation.

b. Quantitative review: hands-on in data validation/ assessment and perform statistical test

e. Ensuring the model is fit for use as per the Bank’s Model Risk Management framework

f. Collaborate with various stakeholders, e.g. Model Developer, Model Owner, Data Science team, model vendor etc, for model risk identification and assessment.

g. Propose model risk mitigation solution and recommend improvements

h. Improve Model Risk Management framework to embed industry best practice. Ensure the model validation standard meets regulatory guidelines/ requirements

2. Work effectively as a team member with other quantitative analysts in the Bank, as well as with external consultants.

3. Validate IFRS9/ Basel models not limited to PD, LGD, EAD etc.

4. Work with counterparts to perform model FEAT assessment in accordance to MAS guideline

5. Synchronise with group-wide frameworks, processes (including modelling), tools and reporting which support the desired outcomes for risk modelling and capital optimization.

Must Haves

• Passionate in Data which includes ETL, analyse, and interpret data patterns within a complex data environment
• Well versed in credit modelling and/ or data science techniques (AI/ ML models) which includes hands‑on model development and implementation
• Highly proficient in coding (Python/ SQL or R etc); familiar with modern and emerging technology techniques and an interest to stay abreast of industry developments (e.g. DevOps, MLOps, Cloud, APIs, service‑oriented architectures etc).
• At least 2 years / 5+ years of work experience in quantitative modelling, numerical simulation, and data analysis.
• Team orientation and ability to work in a fast paced environment.
• Strong quantitative problem solving skills. Advanced degree in a quantitative discipline such as statistics, data science, maths, physics, engineering, computer science, or financial engineering