Lead Data Scientist - Fraud Analytics / AML | Banking / BFSI

Location : Chennai (Onsite)

Experience : 8 - 12 years

Industry : Banking / BFSI / FinTech / Payments

About the Role :

We are looking for a hands-on Lead - AI & Data Science professional to drive AI and Data Science initiatives within the banking domain.

The role will primarily focus on Fraud Analytics, AML, Transaction Monitoring, Machine Learning model development, deployment and production ownership, while supporting Enterprise AI initiatives.

Key Responsibilities :

- Own and enhance fraud detection platforms, including RBIH MuleHunter, and related AI/ML solutions.

- Develop, deploy, monitor and optimize machine learning models for fraud detection, risk analytics and other banking use cases.

- Manage the complete ML model lifecycle, including validation, tuning, retraining and performance monitoring.

- Develop and optimize fraud detection rules and scenarios using Business Rules Engines (BRE).

- Analyze false positives, false negatives and model performance to improve fraud detection effectiveness.

- Collaborate with business, technology, risk and compliance teams to deliver AI-driven solutions.

- Support Enterprise AI initiatives, AI governance and future AI adoption.

Mandatory Skills & Experience :

- 10+ years of overall experience, including a minimum of 5 years in Machine Learning, Data Science or Advanced Analytics.

- Experience in Banking, BFSI, FinTech or Payments.

- Exposure to Fraud Analytics, AML or Transaction Monitoring.

- Strong hands-on experience in Python, SQL, Machine Learning and Predictive Analytics.

- Experience in classification models, anomaly detection, feature engineering and model validation.

- Proven experience in production ML model deployment, monitoring and optimization.

- Ability to independently manage AI/ML solutions and work with cross-functional stakeholders.

Preferred Skills :

- Experience with MuleHunter, fraud detection platforms or Business Rules Engines.

- Exposure to MLOps, AI Governance and Enterprise AI platforms.

- Understanding of GenAI, LLMs, RAG or Agentic AI.

- Experience in financial crime analytics, risk analytics or banking compliance.

Ideal Candidate :

A hands-on AI/ML professional from a BFSI background who can independently develop and manage production machine learning solutions, with strong exposure to fraud analytics and banking risk management.