Fraud Data Analyst - SQL-Powered Fraud Prevention

Sezzle; United States; Remote; USD 32,000 - 42,000; Full time

Job summary

Sezzle is seeking a Fraud Data Analyst to join our growing team in the United States. You will identify, investigate, and prevent fraudulent transactions, leveraging SQL and Python to analyze large datasets and detect emerging fraud patterns.

The role focuses on protecting customers and Sezzle from financial loss while enabling secure, efficient payments. English resumes required; you will work in a fast-paced fintech environment.

Qualifications

• Bachelor's degree in Economics, Computer Science, Analytics, or a related field.
• At least 2 years of experience in fraud detection, prevention, or investigations.
• At least 2 years of SQL and Python experience.
• Strong analytical and problem-solving skills with attention to detail.
• Experience with fraud typologies and detection tools is a plus.
• Excellent written and verbal communication; able to work independently.

Responsibilities

• Monitor transactions and accounts to identify suspicious activity.
• Use fraud detection tools to identify trends and patterns.
• Conduct in-depth investigations and document findings.
• Analyze large datasets with SQL to spot anomalies.
• Develop and implement fraud prevention rules and controls.
• Stay updated on best practices and new detection technologies.

Skills

SQL

Python

Fraud detection

Data analysis

Education

Bachelor's degree

Tools

Fraud detection platforms

Job description

Sezzle is seeking a Fraud Data Analyst to join our growing team in the United States. You will identify, investigate, and prevent fraudulent transactions, leveraging SQL and Python to analyze large datasets and detect emerging fraud patterns.

The role focuses on protecting customers and Sezzle from financial loss while enabling secure, efficient payments. English resumes required; you will work in a fast-paced fintech environment.