Analyst, Risk Data Scientist

TNG Digital Sdn Bhd; Kuala Lumpur; Hybrid; MYR 100,000 - 180,000; Full time

Job summary

TNG Digital Sdn Bhd in Kuala Lumpur seeks a Risk Data Scientist to build and maintain data-driven solutions for identifying and mitigating fraud and credit risks across the e-wallet platform. You will design risk rules, analyze large datasets with SQL-based analytics, and leverage AI-powered tools to accelerate modelling and reporting.

The role collaborates with risk operations, engineering, product, and BI teams, and involves mentoring juniors while continuously improving detection pipelines

Responsibilities

• Build and calibrate risk rules and decision frameworks for fraud and credit risk mitigation across e-wallet products.
• Analyze large-scale transaction datasets to uncover fraud patterns and anomalous user behaviours with SQL-based analytics.
• Apply statistical methods to quantify risk exposure and establish data-driven thresholds for automated decisioning.
• Improve fraud detection pipelines from data ingestion to feature engineering and rule calibration.
• Collaborate with risk operations, engineering, product, and BI teams to deploy detection solutions.
• Mentor junior colleagues on analytical methods, AI-augmented workflows, and code review best practices.
• Propose data-backed strategies to strengthen fraud and payment risk posture across the platform.
• Stay current with advancements in fraud detection, ML, and AI tooling relevant to fintech risk.
• Produce clear reports and dashboards communicating risk findings and model performance to stakeholders.

Skills

SQL

LLM assistants

AI copilots

Tools

SQL

LLM assistants

AI copilots

Job description

Analyst, Risk Data Scientist##### Contact usLoginBack# Analyst, *Risk Data Scientist*NEWKuala Lumpur, MalaysiaPermanent#### Duties & Responsibilities* A Risk Data Scientist in Fraud & Payment Risk is responsible for building and maintaining data-driven solutions to identify, analyze, and mitigate fraud and credit risks across TNGD’s e-wallet platform. This role combines traditional data science with active use of AI-powered tools to accelerate modelling, analysis, and decision-making.* Build Models and Algorithms:* Design and calibrate risk rules and decision frameworks for fraud and credit risk mitigation across e-wallet products, including merchant risk monitoring and BNPL onboarding assessments.* Leverage AI-powered tools (e.g., LLM assistants, AI code copilots, generative AI) as part of the day-to-day analytics and modelling workflow — from exploratory data analysis and feature engineering to report generation and documentation.* Data Analysis and Risk Assessment:* Analyze large-scale transaction datasets to uncover fraud patterns, merchant risk indicators, and anomalous user behaviours using SQL-based analytics on cloud data platforms.* Apply statistical methods to quantify risk exposure, measure fraud impact, and establish data-driven thresholds for automated decisioning.* Process Improvement:* Continuously improve fraud detection pipelines — from data ingestion and feature engineering to rule calibration and decisioning — ensuring detection methods remain effective against evolving fraud tactics.* Collaboration and Mentoring:* Collaborate with risk operations, engineering, product, and BI teams to integrate detection solutions into production workflows and align risk strategies with business objectives.* Contribute to team knowledge development through mentoring junior colleagues on analytical methods, AI-augmented workflows, and code review best practices.* Propose data-backed strategies and rule enhancements to strengthen fraud and payment risk posture across the platform.* Partner with engineering teams to operationalize models and rules, ensuring reliable deployment and minimal false-positive impact.* Innovation and Learning:* Stay current with advancements in fraud detection, machine learning, and AI tooling — including emerging fraud techniques and new AI/ML applications relevant to fintech risk.* Proactively identify opportunities to apply AI-driven approaches and automation to enhance existing fraud prevention and risk assessment workflows.* Reporting and Communication:* Produce clear, actionable reports and dashboards to communicate risk findings, model performance, and strategy recommendations to stakeholders and senior management.* Translate analytical insights into concrete recommendations that influence risk strategy decisions and regulatory compliance.#### Requirements* As per JDApply Now