fraud analyst

CRED is an exclusive community for India's most trustworthy and creditworthy individuals, where members are rewarded for good financial behavior.

As a fraud analyst at CRED, you'll work at the intersection of data, technology, and fraud prevention to identify and prevent emerging fraud patterns across products.

Responsibilities

Fraud Detection & Analysis

• Analyse large datasets to identify unusual patterns, behaviors, and signals that could indicate emerging fraud.
• Investigate how fraudsters may be exploiting products, processes, or system vulnerabilities.
• Develop hypotheses, test them through data, and translate findings into practical fraud detection approaches.

Fraud Prevention & Problem Solving

• Work with data science and engineering to identify and close gaps in fraud detection and prevention.
• Identify new signals and approaches that can improve our ability to detect evolving fraud patterns.
• Build and iterate on detection logic and solutions as fraud patterns and attack methods change.

Cross-Functional Execution

• Partner with product and engineering teams across CRED to understand new product flows and identify potential fraud risks.
• Work closely with engineering to implement signals, controls, and other prevention mechanisms.
• Operate across different products and problem statements as fraud is a horizontal problem across CRED.

Continuous Learning

• Stay curious about how systems work and how they can be exploited.
• Learn continuously as new fraud patterns, technologies, and vulnerabilities emerge.
• Bring an adversarial / "hacker" mindset to problem solving, think beyond the obvious solution, and challenge existing assumptions.

Requirements

• Have 1–2 years of experience in data science, analytics, engineering, or a related technical role.
• Have strong SQL and analytical skills and are comfortable working with large datasets.
• Have good hands-on Python/coding experience.
• Have a basic understanding of data science/ML concepts such as features, models, and how models are deployed.
• Are highly curious and willing to learn, especially in ambiguous and unfamiliar problem spaces.
• Have an adversarial / hacker mindset.
• Are comfortable getting hands-on and working closely with engineering and product to take an idea from analysis to implementation.
• Have strong ownership and grit, and are comfortable operating with urgency when the problem demands it.