Job Title : Director - Fraud Risk Strategy & Analytics (Hands-On Technical Lead)

Location : Bangalore, Gurugram, and Hyderabad (Hybrid)

Experience : 10+ Years

Job Summary :

We are seeking a strategic, quantitative, and technically hands-on Director - Fraud Risk Strategy & Analytics to lead delivery for top-tier global banking and payment partners. In this role, you will be active in code, ML modeling, and technical reviews while leading a team of risk strategy analysts to design end-to-end fraud risk strategies and manage credit settlement/network integrity risks. This is a partially hands-on role requiring recent, active technical experience in Python and SQL alongside leadership expertise.

Key Responsibilities:

1. Technical & Team Leadership:

- Lead and mentor a team of 5-10 risk strategy analysts and modeling professionals, maintaining an active, hands-on role in technical code reviews, feature engineering, and model validation.

2. Hands-On Fraud Strategy & ML Modeling:

- Lead and directly participate in developing, deploying, and optimizing fraud decision rules and predictive machine learning models (e.g., ATO, Transactional Fraud, CNP, P2P/C2B).

3. Credit Settlement & Counterparty Risk:

- Manage counterparty settlement risk across merchant acquirers and payment networks, developing exposure models, rolling reserve frameworks, and chargeback triggers.

4. Network Integrity & Authorization Optimization:

- Oversee payment network rules and compliance programs (Visa, Mastercard) while optimizing authorization rates and minimizing false positive rates.

5. Executive Stakeholder Management :

- Serve as a strategic technical liaison for global financial institutions, translating technical ML findings into clear business decisions.

Required Qualifications :

- Experience: 10+ years in fraud risk strategy, fraud modeling, or credit risk within Financial Institutions, Card Networks, Issuing Banks, or Payment Gateways.

- Mandatory Technical Recency: Must have active hands-on technical involvement in SQL and Python within the past 1-2 years. Candidates seeking a purely managerial role will not be considered.

- Technical Skills: Advanced SQL (complex joins, optimization for large transaction volumes) and Python (Pandas, NumPy, Scikit-Learn for EDA, feature engineering, and validation).

- Domain Expertise: Proven track record leading ML risk modeling projects, fraud strategy design, credit settlement risk, and payment network integrity frameworks.

- Education: Bachelor's or Master's in Statistics, Economics, Finance, Mathematics, Computer Science, or a related quantitative field will be preferred but not mandatory.