- Salary
- $2k – $2k
- Location
- Mexico
- Workplace
- Remote
- Type
- Full-time
- Department
- DS-Risk & Fraud
- Experience
- 1+ years
- Education
- Bachelor
- Source
- Greenhouse
Description
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 talented and motivated Fraud Operations Analyst who is best in class with a high IQ plus a high EQ. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement. As part of optimizing the online shopping experience, Sezzle constantly monitors users and transactions for abusive or fraudulent behavior. Our Fraud Operations team reviews suspicious activity flagged by Sezzle’s fraud detection system or escalated from Customer Support agents. Fraud Operations Analysts will block users deemed fraudulent or risky, and clear false positive flags from our automated systems and support agents. We monitor for new trends in fraudulent behavior and continuously evolve our policies and procedures to stay one step ahead. We are looking for a teammate who can work one of the shifts listed below full-time:
- Monday to Friday, 3:00 PM to 11:30 PM - Central Time
This will be a non-exempt/hourly position. Due to the requirements of the position, only English resumes will be accepted.
Compensation:
For this Fraud Operations Analyst the compensation range is $1,500 - $2,000 USD GROSS per month as a contractor. This range is designed to reflect the skills, experience, and value brought to the team, ensuring competitive and fair pay within the industry.
What You'll Do:
- Monitor real-time transactions and other customer behaviors flagged for fraud and abuse for manual review.
- Investigate individual transactions using internal policies and review methodologies to determine if the transactions are fraudulent or not.
- Understand our systems and tools; investigate account patterns through data analysis.
- Research fraud and user behavior to contribute to machine learning models, rules and other detection systems.
- Collaborate with analysts, operations specialists, data scientists and engineering to improve our fraud prevention mechanisms, processes and tools.
- Learn and maintain strong domain knowledge of the world of fraud including prevention techniques and technologies.
- Maintain or exceed established service level agreements (SLAs) for timely resolution of queued cases to minimize potential losses.
- Handle escalations from internal and external stakeholders in a professional and efficient manner.
What We Look For:
- Bachelor's degree from an accredited institution
- Minimum 1 year of experience in investigating and resolving fraud incidents
- Experienced in analyzing data and comfortable making impactful decisions in a fast-paced and sometimes ambiguous environment
- Attention to detail and ability to multitask
- Excellent problem-solving and analytical skills
- Strong business judgment and communication skills
- Ability to self-start and work with minimal supervision after training
- Able to work through holidays
- 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
- Experience in using database query language (e.g. SQL, etc), and data processing and analytics tools such as Python / R / SAS is a plus
- Ideal candidate will be available to start within two weeks following an offer
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 action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
- You earn trust - you listen attentively, speak candidly, and treat others respectfully.
- You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
- You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.
What Makes Working at Sezzle Awesome:
At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators. We believe in surrounding ourselves with only the best and the brightest individuals. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.
#Li-remote #Full-Time
Skills
PythonSQLMachine LearningR