Senior Fraud Data Analyst

Moniepoint; Town of Poland (NY); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Moniepoint is seeking a Data Analyst (Fraud) in the United States to investigate attacks, quantify impact, and translate insights into action. You’ll work with fraud operations, data scientists, engineers, and product managers to refine mitigations and monitor risk.

Ideal candidates have 4+ years in fraud data analysis, strong SQL, and experience with BI tools. A proactive, collaborative mindset and a relevant degree are essential for success in a fast-changing, cross-functional environment.

Qualifications

• Proven experience as a Data Analyst (Fraud) or similar role (4+ years).
• Advanced SQL with ability to craft complex queries over large datasets.
• Fraud, risk, or financial services experience and mitigation thinking.
• Proactive mindset with data-driven decision making.
• Some Python or scripting for data manipulation and analysis.
• Experience with a BI tool (PowerBI/Looker/Tableau/Superset/Redash).
• Strong stakeholder management and clear communication with teams.
• Comfort in fast-paced, cross-functional environments.
• Proficiency with spreadsheet tools (Excel/Sheets).
• Bachelor’s degree in CS/Statistics/Math/Engineering or related field.

Responsibilities

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

Skills

SQL

Data analysis

Fraud knowledge

Python

BI tools

Stakeholder mgmt

Communication

Excel

Education

Bachelor's in CS/Stats/Math

Tools

PowerBI

Looker

Tableau

Superset

Redash

Job description

Moniepoint is seeking a Data Analyst (Fraud) in the United States to investigate attacks, quantify impact, and translate insights into action. You’ll work with fraud operations, data scientists, engineers, and product managers to refine mitigations and monitor risk.

Ideal candidates have 4+ years in fraud data analysis, strong SQL, and experience with BI tools. A proactive, collaborative mindset and a relevant degree are essential for success in a fast-changing, cross-functional environment.