Get to know our Company:

GX Bank Berhad - the Grab-led Digital Bank - is the FIRST digital bank in Malaysia, approved by BNM to commence operations. We aim to leverage technology and innovation to serve the financial needs of the unserved and underserved individuals, and micro and small medium enterprises.

We are driven by our shared purpose and passion to bring positive transformation to the banking industry, starting with solutions that address the financial struggles of Malaysians and businesses.

Get to know the Role:

• Manage and complete the model validation from end to end for new/ existing models in the bank, which covers:
  • Qualitative review: underlying model assumptions and algorithms, i.e. supervised learning and unsupervised learning models, use of model & its interpretation;
  • Quantitative review: hands-on in data validation/ assessment and perform statistical test;
  • Review model documentation;
  • Perform model stress testing;
  • Ensuring the model is fit for use as per the Bank’s Model Risk Management framework;
  • Collaborate with various stakeholders, e.g. Model Developer, Model Owner, Data Science team, model vendor etc, for model risk identification and assessment;
  • Propose model risk mitigation solution and recommend improvements;
  • Improve Model Risk Management framework to embed industry best practice; and
  • Ensure the model validation standard meets regulatory guidelines/ requirements.
• Work effectively as a team member with other quantitative analysts in the Bank, as well as with external consultants.
• Validate IFRS9/ Basel models not limited to PD, LGD, EAD etc.
• Work with GXS Singapore counterparts to perform model FEAT assessment in accordance with MAS guideline.
• Synchronise with group-wide frameworks, processes (including modelling), tools and reporting which support the desired outcomes for risk modelling and capital optimization.

The 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 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.
• CFA / FRM / BRM / Chartered Banker would be added advantage.