Fraud Data Analyst

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Oversee transactions and customer accounts to detect and investigate any suspicious or fraudulent activities.

• Employ fraud detection tools, systems, and methodologies to uncover new fraud trends and patterns.

• Perform thorough investigations into suspected fraudulent actions, collecting evidence and documenting results.

• Analyze extensive datasets using SQL to pinpoint anomalies, patterns, and insights associated with fraudulent behavior.

• Create and implement fraud prevention rules, strategies, and controls.

• Keep abreast of industry best practices, emerging fraud threats, and advancements in fraud detection and prevention technologies.

⛳️ Requirements

• A bachelor's degree in a relevant discipline (e.g., Economics, Computer Science, Analytics, or a similar field).

• At least two (2) years of experience in fraud detection, prevention, or investigation roles.

• Minimum of two (2) years of experience with SQL and Python.

• Exceptional analytical and problem-solving abilities, with a strong attention to detail.

• Knowledge of common fraud typologies, such as account takeover, identity theft, and payment fraud.

• Experience with fraud detection tools and platforms is advantageous.

• Outstanding written and verbal communication skills, capable of clearly explaining complex issues.

• Ability to work autonomously and collaboratively within a team in a dynamic environment.

• Strong organizational capabilities and the ability to manage multiple priorities efficiently.

• A high level of integrity and a commitment to ethical practices.

• Proven experience with Claude or equivalent large language model tools is essential.

• Must be proficient in utilizing AI to boost productivity, research, and communication.

• Only resumes in English will be considered.

🏝️ Benefits

• Sezzle culture that values purpose-driven, unique, and innovative employees.

• Remote work opportunity (Argentina, Remote).

• Full-time employment.