- Salary
- $2k – $2k
- Location
- Bogota, Colombia
- Workplace
- Remote
- Type
- Full-time
- Department
- DS-Risk & Fraud
- Experience
- 1+ years
- Education
- Bachelor
- Source
- Greenhouse
Description
About the Role:
Sezzle is seeking a Fraud Operations Analyst to support fraud monitoring. 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 - Friday between 3:00 PM - 11:30 PM Central Time.
This will be a non-exempt/hourly position.
Compensation:
$2,000 USD per month.
Our Company
Sezzle is a cutting-edge fintech company whose long-standing mission is to financially empower the next generation. Only one in three millennials own a credit card, and the vast majority of millennials possess a subprime credit score or no score at all. To address these problems, Sezzle has built a payment platform that increases purchasing power for consumers by offering interest-free installment plans at online stores. This increase in purchasing power for consumers leads to increased sales and basket sizes for the numerous eCommerce merchants that currently work with Sezzle.
As the first and only B-Corp in the payments space, Sezzle’s goal is to help everyone pursue financial freedom, and to invest in social good and ethical initiatives that shape a better world.
At Sezzle, we’re committed to putting purpose alongside profitability. We work hard to maintain rigorous standards of social and environmental performance, accountability, and transparency to build a better world. The employees at Sezzle lean into significant societal and cultural shifts, ensuring internal and external focus on positive impacts that benefit our community.
Responsibilities:
- 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.
Ideal Skills & Experience:
- 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
- Minimum GPA of 3.5 out of 4.0
- 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:
- A+ character. We are team-first here at Sezzle.
- A hard-working mentality. It’s early and there is still a lot to build.
- An excellent communicator.
- A fun attitude. Life’s too short. We can have fun while we work hard on cool things.
- Smarts. We need people that are smart enough to make decisions on their own and also smart enough to know when they need input from others.
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 are skilled musicians, yogis, cyclists, chefs, golfers, dog-lovers, and rock-climbers. We believe in surrounding ourselves with not only the best and the brightest individuals, but those that are unique and purpose-driven in all that they do. Sezzle recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting our mission.
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.
Sezzle provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, creed, gender, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, national origin, age, disability, genetic information or characteristics, marital status, familial status, veteran or military status, status regarding public assistance, membership or activity in a local commission, or any other protected status in accordance with applicable federal, state and local laws.
Skills
PythonSQLMachine LearningR