Fraud Data Analyst (Fintech)

TL;DR

Fraud Data Analyst (Fintech): Investigating and preventing fraudulent transactions by monitoring accounts, utilizing fraud detection tools, and analyzing large datasets with SQL. Focus on developing fraud prevention strategies and controls to protect the company and customers from financial loss.

Location: Remote

Company

hirify.global is revolutionizing the shopping experience beyond payments with interest-free installment plans.

What you will do

• Monitor transactions and customer accounts to identify and investigate suspicious or fraudulent activity.
• Utilize fraud detection tools and techniques to identify emerging fraud trends and patterns.
• Conduct in-depth investigations into suspected fraudulent activities, gathering evidence and documenting findings.
• Analyze large datasets using SQL to identify anomalies, patterns, and insights related to fraudulent behavior.
• Develop and implement fraud prevention rules, strategies, and controls.
• Stay up-to-date with industry best practices, emerging fraud threats, and new technologies in fraud detection and prevention.

Requirements

• Bachelor's degree in a relevant field (e.g. Economics, Computer Science, Analytics, or a related field).
• Minimum of two (2) years of experience in a fraud detection, prevention, or investigation role.
• Minimum of two (2) years of experience working with SQL and Python.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Understanding of common fraud typologies (e.g., account takeover, identity theft, payment fraud, etc.).
• English resumes only.

Nice to have

• Work experience in fintech, payments, lending, banking, or financial institutions.
• Degree in statistics, math, finance, economics, or related quantitative discipline; graduate degree.

Culture & Benefits

• Dynamic, fast-paced environment with opportunities for career advancement.
• A culture that values innovation, collaboration, and delivering results.
• A team of brilliant engineers, passionate data enthusiasts, and out-of-the-box thinkers.
• Focus on developing new ways to do things and calculated risk-taking.
• Emphasis on earning trust, respectful communication, and commitment to decisions.