Salary not disclosed
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Role overview
Job description
fraud detection & analysis:
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analyse large datasets to identify unusual patterns, behaviours and signals that could indicate emerging fraud.
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investigate how fraudsters may be exploiting products, processes or system vulnerabilities.
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develop hypotheses, test them through data and translate findings into practical fraud detection approaches.
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work with data science and engineering to identify and close gaps in fraud detection and prevention.
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identify new signals and approaches that can improve our ability to detect evolving fraud patterns.
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build and iterate on detection logic and solutions as fraud patterns and attack methods change.
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partner with product and engineering teams across cred to understand new product flows and identify potential fraud risks.
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work closely with engineering to implement signals, controls and other prevention mechanisms.
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operate across different products and problem statements as fraud is a horizontal problem across CRED.
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stay curious about how systems work and how they can be exploited.
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learn continuously as new fraud patterns, technologies and vulnerabilities emerge.
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bring an adversarial / "hacker" mindset to problem solving , think beyond the obvious solution and challenge existing assumptions.
fraud prevention & problem solving:
cross-functional execution:
continuous learning:
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have 1–2 years of experience in data science, analytics, engineering or a related technical role.
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have strong sql and analytical skills and are comfortable working with large datasets.
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have good hands-on python/coding experience.
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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.
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are highly curious and willing to learn, especially in ambiguous and unfamiliar problem spaces.
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have an adversarial / hacker mindset you naturally think about how a system might be broken, exploited or circumvented.
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are comfortable getting hands-on and working closely with engineering and product to take an idea from analysis to implementation.
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have strong ownership and grit, and are comfortable operating with urgency when the problem demands it.
how is life at CRED? working at CRED would instantly make you realize one thing: you are working with the best talent around you. not just in the role you occupy, but everywhere you go. talk to someone around you; most likely you will be talking to a singer, standup comic, artist, writer, an athlete, maybe a magician. at CRED people always have talent up their sleeves. With the right company, even conversations can be rejuvenating. at CRED, we guarantee a good company. hard truths: pushing oneself comes with the role. and we realize pushing oneself is hard work. which is why CRED is in the continuous process of building an environment that helps the team rejuvenate oneself: included but not limited to a stacked, in-house pantry, with lunch and dinner provided for all the team members, paid sick leaves and a comprehensive health insurance. to make things smoother and to make sure you spend time and energy only on the most important things, CRED strives to make every process transparent: there are no work timings because we do not believe in archaic methods of calculating productivity, your work should speak for you. there are no job designations because you will be expected to hold down roles that cannot be described in one word. there are many more such eccentricities that make CRED what it is but that’s for one to discover. if you feel at home reading this, get in touch.
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About this listing
- Source: CRED's official careers site · still listed there on 12 Nov 2026
- Posted 5 Nov 2026
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What they are looking for
Skills & requirements
Qualification
you should apply if you: have 1–2 years of experience in data science, analytics, engineering or a related technical role
Department · Data Science
Hiring company
CRED
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