Fraud Risk Analyst: Data-Driven Guardian of Trust

Shield 1; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

SHIELD is a device-first fraud intelligence platform helping digital businesses worldwide to eliminate fake accounts and stop fraudulent activity. The Risk Analyst will analyze large datasets to identify fraud trends and design long-term risk solutions, coordinating with stakeholders to drive trust for clients.

Responsibilities include end-to-end data analysis, monitoring risk deployments, responding to alerts, and deep-diving into metric changes to prevent fraud, using device, user and payment

Qualifications

• 1–3 years of hands-on analyst experience with risk knowledge.
• Bachelor’s degree in Computer Science, Data Sciences, Statistics, Mathematics, or related fields.
• Experience handling large-scale unstructured data.
• Experience in BI tools such as Excel, Tableau, and Qlik Sense.
• SQL or other data handling tools is a bonus.

Responsibilities

• Handle end to end process from data analysis, deriving insights, summarizing, and presenting recommended actions to stakeholders in order for us to stay ahead of new and unknown fraud.
• Monitor any new or existing risk-related deployments and metrics for our clients and their potential fraud trends.
• Timely response to alerts for risk-related escalations.
• Deep dive investigation on potential issues such as changes to clients’ metrics, and coordinate with stakeholders to ensure timely resolution.
• Optimize fraud detection by data-driven analysis on device metadata, user data, and payment data to propose and address emerging fraud trends.

Skills

Data analysis

Risk knowledge

Analytical mindset

Education

Bachelor's degree in Computer Science / Data Sciences / Statistics / Mathematics

Tools

Excel

Tableau

Qlik Sense

SQL

Job description

SHIELD is a device-first fraud intelligence platform helping digital businesses worldwide to eliminate fake accounts and stop fraudulent activity. The Risk Analyst will analyze large datasets to identify fraud trends and design long-term risk solutions, coordinating with stakeholders to drive trust for clients.

Responsibilities include end-to-end data analysis, monitoring risk deployments, responding to alerts, and deep-diving into metric changes to prevent fraud, using device, user and payment