Fraud Data Analyst
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The salary range for this role is $2,900 - 3,750 per month (Gross in USD)
About Sezzle:
With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!
About the Role:
We are seeking a detail-oriented and analytical Fraud Data Analyst to join our growing team. The ideal candidate will have a passion for uncovering fraudulent activities and a strong understanding of fraud prevention strategies. In this role, you will be responsible for identifying, investigating, and preventing fraudulent transactions and activities, utilizing your analytical skills and experience with SQL to query and analyze data. You will play a crucial role in protecting our company and our customers from financial loss and reputational damage.
Due to the requirements of the position, only English resumes will be accepted.
What You'll Do:
Monitor transactions and customer accounts to identify and investigate suspicious or fraudulent activity. Utilize various fraud detection tools, systems, 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.
What We Look For:
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.). Experience with fraud detection tools and platforms is a plus. Excellent written and verbal communication skills, with the ability to clearly articulate complex issues. Ability to work independently and as part of a team in a fast-paced environment. Strong organizational skills and the ability to manage multiple priorities effectively. High level of integrity and a commitment to ethical practices Demonstrated experience working with Claude or equivalent large language model tools is required; candidates must be comfortable leveraging AI to enhance productivity, research, and communication.
Preferred Qualifications
Work experience in fintech, payments, lending, banking, or financial institutions is a plus Degree in statistics, math, finance, economics, or related quantitative discipline; graduate degree a plus
About You:
You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed. You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things You need...
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About Sezzle
Learn more about Sezzle and their company culture.
Buy now, pay later company that lets shoppers split purchases into interest-free installments.
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