Get To Know Our GX Bank TeamGX 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

The incumbent will focus on analyzing risk-related data, identifying trends, and providing actionable insights to enhance risk management strategies. The ideal candidate will have strong analytical skills, experience with statistical modeling, and a deep understanding of financial risk metrics.

Key Responsibilities:

• Analyze large datasets to identify trends, anomalies, and risk patterns related to credit, fraud, operational, and market risks.

• Develop risk models and perform predictive analytics to support proactive risk mitigation strategies.

• Generate insights from structured and unstructured data to improve decision-making and risk assessment processes.

• Work closely with risk management and business teams to define key risk indicators (KRIs) and develop automated monitoring systems.

• Build and maintain risk reporting frameworks, dashboards, and visualizations to communicate risk trends effectively.

• Support the development of machine learning models for fraud detection and risk scoring.

• Ensure data integrity and accuracy in risk analysis and reporting processes.

• Conduct scenario analysis and stress testing to assess potential risk exposures under different economic conditions.

• Stay updated on regulatory requirements, industry trends, and emerging risks in digital banking

Requirements:

• Bachelor's degree in Data Science, Business Analytics, Finance, Statistics, Computer Science, or a related field. A Master’s degree is a plus.

• 3+ years of experience in risk analytics, data science, or business intelligence, preferably in financial services or fintech.

• Proficiency in SQL, Python, R, or other statistical tools for risk analysis.

• Experience with data visualization tools such as Power BI, Tableau, or related tools.

• Strong knowledge of risk management principles, financial risk metrics, and regulatory reporting frameworks.

• Hands-on experience with machine learning models and predictive analytics techniques.

• Ability to work with large datasets and perform ETL (Extract, Transform, Load) processes.

• Strong problem-solving, critical thinking, and communication skills.

• Ability to translate complex data into meaningful risk insights for business stakeholders.