Remote Fraud Risk Operations Intern

Sezzle; Santiago; Remote; CLP 7,973,000 - 9,550,000; Full time

Job summary

Sezzle is seeking a Fraud Operations Intern to join our Shopper Risk Operations team. You will monitor real-time transactions, investigate suspicious activity, and support improvements to fraud prevention through data analysis and collaboration with analysts, data scientists and engineers.

This paid internship offers hands-on experience in a fast-paced fintech environment, with opportunities to contribute to ML models, rules, and detection systems while learning industry best practices.

Qualifications

• Experience analyzing data and making decisions in fast-paced environments.
• Attention to detail and ability to multitask.
• Excellent problem-solving and analytical skills.
• Strong business judgment and communication skills.
• Ability to start independently after training.
• Experience using Claude or similar LLM tools for productivity and research.

Responsibilities

• Monitor real-time transactions and flags for manual review.
• Investigate transactions using internal policies and determine fraud risk.
• Analyze account patterns and data to understand fraud trends.
• Research fraud and user behavior to contribute to models and rules.
• Collaborate with analysts, data scientists, and engineers to improve detection systems.
• Maintain knowledge of fraud prevention techniques and technologies.
• Meet SLAs to minimize potential losses.
• Handle escalations professionally.

Skills

Data analysis

Attention to detail

Analytical thinking

Communication skills

Self-motivation

Claude AI

Job description

Sezzle is seeking a Fraud Operations Intern to join our Shopper Risk Operations team. You will monitor real-time transactions, investigate suspicious activity, and support improvements to fraud prevention through data analysis and collaboration with analysts, data scientists and engineers.

This paid internship offers hands-on experience in a fast-paced fintech environment, with opportunities to contribute to ML models, rules, and detection systems while learning industry best practices.