Join Snapmint as a Data Analyst in our Fraud Risk Team and help drive end-to-end fraud prevention for high-scale digital lending products. In this role, you'll work on real-time fraud detection, rule building, and data analytics to minimize fraud losses while ensuring a seamless customer experience.
Key Responsibilities:
- Monitor fraud metrics across products including Checkout, EMI, Pay Later, Personal Loans, and UPI Credit
- Identify fraud patterns through deep-dive data analysis
- Build, test, and optimize fraud rules within decisioning systems
- Collaborate with technology teams to deploy real-time fraud controls
- Support fraud model development using internal, bureau, and third-party data
- Partner with Fraud Operations to investigate trends and improve fraud detection
- Track rule and model performance to reduce false positives while maintaining strong fraud capture.
Requirements - Must-Have
- 2–5 years of experience in Fraud Risk or Risk Analytics (fintech or digital lending experience preferred)
- Strong understanding of the credit lifecycle and underwriting
- Proficiency in SQL, Python or R (including libraries such as Pandas and Matplotlib), and Excel
- Strong analytical, problem-solving, and data interpretation skills
- Experience in fraud rule creation and strategy tuning is an advantage
- Hands-on experience with dashboarding tools such as Databricks and Tableau
Requirements - Good to Have
- Exposure to fraud tools and rule engines
- Experience working with third-party data providers (credit bureaus, device intelligence, etc.)
- Basic understanding of machine learning models used in fraud detection
What Makes You a Great Fit
- Hands-on approach with a robust sense of ownership
- Ability to balance effective fraud prevention with an excellent customer experience
- Comfortable working in a fast-paced, high-growth startup environment