Data Analyst - Fraud Risk Management

About Snapmint:

India's booming consumer market has over 300 million credit-eligible consumers, yet only 35 million actively use credit cards. At Snapmint, we are building a better alternative to credit card that lets consumers buy now and pay later for a wide variety of products, be it shoes, clothes, fashion accessories, clothes or mobile phones. We firmly believe that an enduring financial services business must be built on the bedrock of providing honest, transparent and fair terms.

Founded in 2017, today we are the leading online zero-cost EMI provider in India. We have served over 10M consumers across 2,200 cities and are doubling year on year. Our founders are serial entrepreneurs and alumni of IIT Bombay and ISB with over two decades of experience across leading organizations like Swiggy, Oyo, Maruti

Suzuki and ZS Associates before successfully scaling and exiting businesses in patent analytics, ad-tech and bank tech software services.

Role Overview:

We are looking for a Data Analyst to join Snapmint's Fraud Risk team and drive end-to-end fraud prevention for high-scale digital lending products. In this role, you will work on real-time fraud detection, rule building, and data driven analytics to minimize fraud losses while ensuring a seamless customer experience.

Key Responsibilities:

• Monitor fraud metrics across products (Checkout, EMI, Pay Later, Personal Loans, UPI Credit)

• Identify fraud patterns via deep-dive data analysis

• Build, test, and optimize fraud rules in decisioning systems

• Collaborate with tech teams to deploy real-time fraud controls

• Support fraud model development using internal, bureau, and third-party data

• Work with Fraud Ops to investigate trends and improve detection

• Track rule/model performance; reduce false positives while maintaining fraud capture

Qualifications:

• 2-5 years of experience in Fraud Risk, Risk Analytics, or related roles, preferably in fintech or digital lending

• Strong understanding of credit lifecycle, underwriting, and fraud risk management strategies

• Proficiency in SQL, Python/R, Excel, and dashboarding tools such as Tableau or Databricks

• Strong analytical, problem-solving, and fraud rule creation/strategy tuning capabilities

• Self-driven and adaptable professional with a high-ownership mindset and the ability to balance fraud prevention with customer experience in a fast-paced environment