Job Location: Bangalore

Team: Risk & Data Science

About Zype

Zype is a credit-first financial well-being & lifestyle app. We help our customers make their aspirational lifestyle affordable while helping them make responsible financial decisions & positively contribute to their financial well-being.

With a fully digital & seamless user experience, we are helping the next generation of credit users get instant loan & always have access to money when they need it. This combined with Zype’s intuitive money management tools can help them manage their spending, get bill reminders & make timely payments, all on one single app.

At Zype, we challenge ourselves daily to deliver an exceptional experience to our users. We are passionate about what we do & leverage the latest technology to add outstanding value to the lives of our customers.

Role Overview

We are looking for a Lead – Fraud Risk Analytics to design and implement AI-driven fraud detection systems for UPI, cards, and digital payments. This role requires deep expertise in real-time fraud detection, anomaly detection, behavioral analytics, and AI/ML-based risk modeling. This role will also help build the business intelligence for the UPI vertical.

What You’ll Do

Fraud Detection & Prevention

• Build and enhance real-time fraud detection models for UPI transactions, QR payments, and card transactions.
• Develop AI-driven behavioral risk models to detect abnormal payment activity, device spoofing, and synthetic identity fraud.
• Design rule-based + ML-driven fraud detection systems to reduce false positives & false negatives.
• Implement device intelligence, geo-location tracking, and biometric authentication to prevent fraud.
• Work closely with the engineering team to integrate fraud detection APIs into UPI systems.
  
  

Risk Analytics & Model Development

• Design machine learning models (supervised & unsupervised) for fraud pattern recognition.
• Develop graph analytics models to detect fraud rings, mule accounts, and collusion.
• Implement real-time anomaly detection for transaction velocity, value, and geolocation mismatches.
• Optimize UPI risk scoring frameworks based on RBI & NPCI fraud guidelines.
  
  

Operational & Regulatory Risk Management

• Work with NPCI, RBI, and banking partners to ensure compliance with UPI fraud monitoring regulations.
• Establish risk rules & thresholds for suspicious transactions (e.g., high-frequency transactions, cross-border UPI fraud).
• Monitor fraud trends & suggest real-time interventions for high-risk transactions.
  
  

AI-Driven Chargeback & Dispute Management

• Design AI-driven chargeback prediction models to minimize fraud losses.
• Build an early warning system to flag suspicious refunds and chargeback abuse.
• Automate dispute resolution workflows using NLP-based document analysis.
  
  

Stakeholder & Team Leadership

• Collaborate with product, risk, engineering, and compliance teams to enhance fraud mitigation strategies.
• Mentor & guide a team of fraud analysts, data scientists, and risk engineers.
• Stay updated on global fraud trends, AI-driven fraud strategies, and regulatory changes.
  
  

What We’re Looking For

• Technical Proficiency: Strong foundation in machine learning, statistical analysis, and data modeling techniques.
• Programming Skills: Experience with Python, R, SQL, or similar tools for data analysis. Familiarity with big data platforms like Spark or Hadoop is a bonus.
• Analytical Thinking: Ability to solve complex problems and provide meaningful insights from large datasets.
• Collaboration: Excellent communication and teamwork skills to work effectively with product, engineering, and business teams.
• Domain Knowledge: Have an understanding of BNPL credit risk.
• Attention to Detail: Precision in building models and delivering accurate results.
  
  

Experience & Qualifications

• Experience: 5+ years in data science, analytics, or a related field. 2+ years in UPI, Cards, or Digital Payments
• Educational Background: Bachelor’s or master’s degree in data science, Statistics, Mathematics, Computer Science, or a related discipline.
  
  

Why Zype?

• Impactful Work: Be part of a fast-growing fintech, driving data-driven innovation in BNPL.
• Collaborative Culture: Work alongside talented peers in a supportive and inclusive environment.
• Learning Opportunities: Gain exposure to cutting-edge technologies and methodologies in risk analytics.
• Career Growth: Build your career with opportunities to grow in a high-impact role.
  
  

Ready to redefine risk analytics? Join Zype and shape the future of BNPL in India!