Responsibilities
- Develop and deploy fraud detection, transaction monitoring, and behavioural risk models across payments, accounts, onboarding, and merchant activity
- Design and run experiments to optimise fraud catch rates, false positives, and customer friction
- Partner with product and engineering teams to embed models into real-time decisioning systems
- Build features from high-volume transactional, device, network, and behavioural data
- Continuously monitor model performance, drift, and emerging fraud patterns
- Ensure data quality, governance, and responsible use of models in regulated environments
- Support investigations, strategy, and policy teams with advanced fraud analytics
- Mentor analysts and product teams on experimentation, detection strategy, and data-driven decision making
Requirements
- A strong foundation in statistics with a degree in a quantitative field (Statistics, Mathematics, Engineering, Computer Science, or similar)
- 5+ years of experience in data science, decision science, or risk analytics within fraud, payments, or financial crime
- Hands-on experience with fraud detection, transaction monitoring, or behavioural risk modelling
- Proficiency in SQL and at least one modelling/programming language (Python or R)
- Experience with machine learning, anomaly detection, network/graph features, and real-time decision systems
- Strong intuition for fraud typologies, adversarial behaviour, and evolving attack patterns
- Ability to translate complex analysis into clear, actionable recommendations for technical and non-technical stakeholders
- High ownership mindset and comfort working in fast-paced, cross-functional product environments
Benefits
- Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
- Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
- Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits
Team
Team size: ~100 teammates. Structure: based across Bengaluru, Mumbai, Pune, Chennai, Hyderabad, and Gurgaon
