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Fraud Data Analyst

Sezzle is looking for a skilled and detail-oriented Fraud Data Analyst to join our team offering the opportunity to work remotely from anywhere in Chile. You will play a critical role in protecting Sezzle's platform integrity by analyzing complex transaction data and identifying emerging fraud patterns. Key responsibilities include developing robust fraud detection models, creating insightful dashboards, and collaborating with risk management teams to improve preventative measures. The ideal candidate possesses strong proficiency in SQL, statistical analysis, and Python/R, coupled with practical experience in financial fraud investigation. This role requires a proactive mindset and the ability to translate complex data findings into actionable business intelligence that minimizes losses and enhances user trust.

Sezzle Chile, Remote, Chile

(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)

Preparing

2800

Question set

150

Duration

Permanent

Focus areas

Data AnalysisFraud DetectionSQLMachine Learning

People Also Ask (FAQs)

What is the last date to apply for Fraud Data Analyst?

The closing date is listed in the official advertisement — apply as early as possible.

How do I apply for Fraud Data Analyst?

Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.

Is there negative marking in the greenhouse test?

The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.

What is the passing marks for this test?

The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.

How can I prepare for the Fraud Data Analyst test?

Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Data Analysis, Fraud Detection, SQL, Machine Learning.

Quick start

Review the job summary, then jump into prep with the same flow used for exam starts.

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