Hirecept Mark
Hirecept

CRED

fraud analyst

bengaluru, IN

Role snapshot

CRED is hiring a fraud analyst on a full-time basis. This is a role based in bengaluru, IN. The listing highlights data science and lending.

Company
CRED
Location
bengaluru, IN
Job type
Full-time
Experience
1–2 years
Posted
Nov 5, 2026

Who this role suits

People with roughly one to three years of experience who can own small pieces of work with light guidance and want to widen their scope.

How to prepare your application

  • Check your résumé against the listed skills (data science and lending) and give each one a concrete example: what you built or achieved, not just that you used it.
  • Prepare two or three stories about work you owned end to end, including one thing that went wrong and what you changed.
  • Read what CRED publishes about its product or team, so you can say clearly why this role and this company.

Apply only on CRED's own site. A genuine employer never asks candidates for money, deposits or bank details to apply, interview or “secure” a job. If something looks wrong, use Report a problem with this listing and we will review it. Read how we check listings.

About the role

what will you do?

    fraud detection & analysis:

    • analyse large datasets to identify unusual patterns, behaviours 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.

you should apply if you:

    • 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. you do not need to be an ml specialist or have built fraud models before.

    • are highly curious and willing to learn, especially in ambiguous and unfamiliar problem spaces.

    • have an adversarial / hacker mindset  you naturally think about how a system might be broken, exploited or circumvented.

    • 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.