{"id":3934988,"url":"https://alion.io/job/cred-fraud-analyst","title":"fraud analyst","company":{"id":13702,"name":"CRED","domain":"cred.club","url":"https://alion.io/company/cred","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":89,"open_postings":7,"ghost_share":0,"stale_share":0.429,"repost_share":0,"time_to_fill_p50_days":37,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Finance","role_family":"Finance","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-05T08:36:05Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-08T06:31:25Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"what is CRED?\nCRED is an exclusive community for India’s most trustworthy and creditworthy individuals, where the members are rewarded for good financial behavior. CRED was born out of a need to bring back the focus on a long lost virtue, one of trust, the idea being to create a community centered around this virtue. a community that constantly strives to become more virtuous in this regard till they finally scale their behavior to create a utopia where being trustworthy is the norm and not the exception. to build a community like this requires a community of its own; a community special in its own way, working towards making this vision come true.\nhere’s a thought experiment: what do you get when you put a group of incredibly passionate and driven people and entrust them with the complete freedom to chase down their goals in a completely uninhibited manner? answer: you get something close to what we have at CRED; CRED just has it better.\nhere’s what will be in store for you at CRED once you join as a part of the datascience fraud team:\nrole overview\nas 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.\nfraud patterns continue to evolve, making it important to identify and address emerging risks and vulnerabilities. you’ll think like an adversary -analyse data and system behaviour, spot unusual patterns and vulnerabilities, and work closely with data science, product and engineering teams to build practical solutions that prevent fraud.\nthis is a hands-on problem-solving role. you don’t need to be a fraud expert or a deep ml specialist. what matters is strong analytical and coding fundamentals, curiosity, and the ability to approach problems from first principles.\nwhat will you do?\nfraud detection & analysis:\nanalyse large datasets to identify unusual patterns, behaviours and signals that could indicate emerging fraud.\n\ninvestigate how fraudsters may be exploiting products, processes or system vulnerabilities.\n\ndevelop hypotheses, test them through data and translate findings into practical fraud detection approaches.\n\nfraud prevention & problem solving:\nwork with data science and engineering to identify and close gaps in fraud detection and prevention.\n\nidentify new signals and approaches that can improve our ability to detect evolving fraud patterns.\n\nbuild and iterate on detection logic and solutions as fraud patterns and attack methods change.\n\ncross-functional execution:\npartner with product and engineering teams across cred to understand new product flows and identify potential fraud risks.\n\nwork closely with engineering to implement signals, controls and other prevention mechanisms.\n\noperate across different products and problem statements as fraud is a horizontal problem across CRED.\n\ncontinuous learning:\nstay curious about how systems work and how they can be exploited.\n\nlearn continuously as new fraud patterns, technologies and vulnerabilities emerge.\n\nbring an adversarial / \"hacker\" mindset to problem solving , think beyond the obvious solution and challenge existing assumptions.\n\nyou should apply if you:\nhave 1-2 years of experience in data science, analytics, engineering or a related technical role.\n\nhave strong sql and analytical skills and are comfortable working with large datasets.\n\nhave good hands-on python/coding experience.\n\nhave 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.\n\nare highly curious and willing to learn, especially in ambiguous and unfamiliar problem spaces.\n\nhave an adversarial / hacker mindset you naturally think about how a system might be broken, exploited or circumvented.\n\nare comfortable getting hands-on and working closely with engineering and product to take an idea from analysis to implementation.\n\nhave strong ownership and grit, and are comfortable operating with urgency when the problem demands 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