Fraud Analytics Leader – FinTech Risk & Detection

Mynt; Metro Manila; On-site; PHP 700,000 - 1,200,000; Full time

Benefits offered by this job

Career growth

Competitive compensation

Flexible benefits

Job summary

GCash is seeking a Fraud Strategy & Analytics lead to design and implement advanced fraud detection rules and machine learning models. You will explore large datasets, identify emerging patterns, and monitor KPIs like false positives and fraud rates.

You will collaborate with Product, Engineering, and Support teams to seamlessly integrate fraud controls into the user journey, manage third-party tools, and lead incident investigations to patch vulnerabilities quickly.

Qualifications

• Experience designing fraud detection systems and rules.
• Strong analytical skills with ability to explore large datasets.
• Ability to monitor and improve KPIs like false positives and fraud rates.

Responsibilities

• Strategy & Implementation: Design, implement, and optimize and prioritize fraud detection rules and machine learning models to combat identity theft, account takeover (ATO), and payment fraud.
• Data Exploration: Analyze large datasets to identify emerging fraud patterns and “low-and-slow” attacks that traditional systems might miss.
• Performance Monitoring: Define and track KPIs such as False Positive Rates (FPR), Fraud Rates, and Operational Impact.
• Cross-Functional Leadership: Partner with Product, Engineering, and Customer Support to integrate fraud friction point into the user journey seamlessly.
• Tool Management: Oversee the selection and integration of third-party fraud prevention vendors and internal link-analysis tools.
• Incident Response: Lead the analytical deep-dive during major fraud events to identify the root cause and patch vulnerabilities immediately.
• Quality Assurance: Lead the quality assurance of fraud strategies developed by the analysts. Ensuring all proposed strategies are documented thoroughly, including the business justification, expected impact, and appropriate approvals.

Skills

Fraud detection

Machine learning

Data analysis

KPI tracking

Cross-functional collaboration

Tools

Link-analysis tools

Job description

GCash is seeking a Fraud Strategy & Analytics lead to design and implement advanced fraud detection rules and machine learning models. You will explore large datasets, identify emerging patterns, and monitor KPIs like false positives and fraud rates.

You will collaborate with Product, Engineering, and Support teams to seamlessly integrate fraud controls into the user journey, manage third-party tools, and lead incident investigations to patch vulnerabilities quickly.