Join As Fraud Analyst At CRED | Apply Now

Join As Fraud Analyst At CRED | Apply Now

Job Overview:

Skills: SQL Python Data Analysis Machine Learning Basics Fraud Detection Problem Solving

CRED Hiring Fraud Analyst in Bengaluru | Apply Now

CRED is looking for a Fraud Analyst to join its Data Science Fraud team in Bengaluru. The position is open to technical candidates with 1 to 2 years of experience in analytics, data science, or engineering. You will investigate complex datasets, identify vulnerabilities, and partner with engineering teams to stop fraud.

Who Can Apply?

• Candidates with 1 to 2 years of experience in data science, analytics, engineering, or a related technical domain.
• Professionals with strong SQL capabilities and comfort navigating large datasets.
• Individuals with hands-on coding ability in Python.
• Applicants with a baseline understanding of machine learning concepts like features, models, and deployment.
• Problem solvers with an adversarial mindset who naturally look for system vulnerabilities and loopholes.

About CRED:

CRED is a fintech platform that operates an exclusive community rewarding members for good financial habits and high credit scores. Based in Bengaluru, the organization works on credit, lending, and payments by bringing together high-performing engineering, design, and product talent.

What You Will Do as Fraud Analyst

• Fraud Detection & Data Investigation: Examine high-volume datasets to identify unusual signals, trends, and exploitation patterns across financial products.
• Hypothesis Testing & Signal Design: Formulate hypotheses on emerging attack vectors, test them using data, and turn findings into actionable detection logic.
• Cross-Functional Collaboration: Partner with product and engineering teams across CRED to assess fraud risks in new features and implement controls.
• Continuous Defense Iteration: Learn new fraud tactics as they emerge, explore system weaknesses proactively, and adapt detection mechanisms continuously.

Skills Required:

Data & Querying. Strong SQL skills to extract insights and patterns from extensive datasets.

Programming. Hands-on Python coding ability for data analysis and implementing detection logic.

Machine Learning Fundamentals. Working knowledge of model deployment, features, and evaluation metrics.

Adversarial Problem Solving. Curiosity and mindset to understand how malicious actors might exploit system vulnerabilities.

Basic Qualifications:

• 1–2 years of experience in data science, analytics, engineering, or a related technical role.
• Strong proficiency in SQL with hands-on exposure to querying massive datasets.
• Practical programming experience in Python.
• Basic knowledge of data science and machine learning concepts such as features and models.

Preferred Qualifications:

• Demonstrated ability to move analytical ideas into implementation alongside engineering teams.
• Familiarity with financial systems, product vulnerability discovery, or fraud detection concepts.

Benefits:

• Comprehensive health insurance coverage.
• In-house pantry serving complimentary lunch and dinner.
• Flexible work culture without rigid working hours.
• Paid sick leaves.

Why CRED?

At CRED, you get the freedom to work alongside top talent across industries, tackle challenging horizontal fraud problems across diverse products, and build solutions in an open culture focused on trust and ownership.

How to Prepare

Our tips, based only on what the listing asks for:

• Practice complex SQL queries involving aggregations, window functions, and joins on multi-table datasets.
• Revise Python fundamentals focused on data manipulation, scripting, and exploratory data analysis.
• Think through real-world fraud patterns in fintech (like identity theft or payment exploits) and how you would design signals to catch them.
• Review core machine learning concepts, including feature engineering and evaluating detection logic.

What the Listing Does Not Mention

• Salary or compensation details are not disclosed in the listing.
• Application deadline is not specified.
• Specific college degree or major requirements are not provided.
• Remote or hybrid work arrangement options are not mentioned.

How to Apply: CRED

1. Visit the official CRED job application page on Lever.
2. Fill in your personal information, contact details, and current location.
3. Upload your updated resume or CV.
4. Add links to your LinkedIn, GitHub, or relevant project portfolio.
5. Submit your online application through the portal.

If you enjoy solving complex technical puzzles and thinking like an adversary to protect users, apply for this fraud analytics role at CRED.

Important Links:

Frequently Asked Questions:

What qualification is required?

Required qualification: Technical Graduate. See the eligibility section above for details.

Can complete freshers apply?

The post requires at least 1 to 2 years of relevant experience in analytics, engineering, or data science.

Do I need prior experience in fraud or advanced ML?

No. You do not need to be a fraud specialist or advanced ML researcher, but you must know Python, SQL, and core data science fundamentals.

Where is the work location?

The role is based at CRED's office in Bengaluru.

What are the daily working hours?

CRED does not track fixed working hours; the company assesses team members by their output, ownership, and deliverables.

Stay safe: CRED does not charge any fee to apply or to give an interview. If anyone asks you for money for a job, a referral or an offer letter, it is a scam.

Source: the official CRED careers listing for this role.

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Disclaimer: This job post is for information only. All applications and questions should go to CRED through the official process.

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