Senior Fraud Data Analyst

Moniepoint; United Kingdom; Remote; EUR 65,000 - 95,000; Full time

Benefits offered by this job

Health insurance

Pension

Annual bonus

Job summary

Moniepoint Inc. is a high-growth fintech platform serving millions with payments, banking, and risk tools. We are hiring a Data Analyst (Fraud) to investigate attacks, quantify impact, and build dashboards that monitor fraud trends and mitigations.

You will collaborate with fraud operations, data scientists, engineers, and product managers to translate insights into actionable responses. Ideal candidates have 4+ years in data analytics, strong SQL, and experience in fraud or financial services.

Qualifications

• 4+ years in data analytics, preferably fraud/risk.
• Strong SQL skills for complex data queries and exploration.
• Experience with fraud, risk, or financial services; knowledge of mitigation trade-offs.
• Proactive mindset with ability to identify anomalies independently.
• Some exposure to scripting (Python) for data manipulation.

Responsibilities

• Investigate fraud attacks, quantify impact, and present findings that drive prioritisation and response.
• Propose and refine rule-based mitigations with fraud ops and engineering.
• Build and maintain dashboards to monitor fraud trends, rule performance, and metrics.
• Collaborate with fraud operations, data scientists, engineers, and product managers to turn insights into action.
• Identify emerging patterns and flag risks before they escalate.

Skills

SQL

Python

BI tools

Fraud domain knowledge

Stakeholder management

Communication

Excel

Cross-functional teamwork

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related field

Tools

PowerBI

Looker/Tableau/Superset

Job description

Moniepoint Inc. is a high-growth fintech platform serving millions with payments, banking, and risk tools. We are hiring a Data Analyst (Fraud) to investigate attacks, quantify impact, and build dashboards that monitor fraud trends and mitigations.

You will collaborate with fraud operations, data scientists, engineers, and product managers to translate insights into actionable responses. Ideal candidates have 4+ years in data analytics, strong SQL, and experience in fraud or financial services.