Lead Data Scientist - Artificial Intelligence/Machine Learning Engineering - BFSI - IIT/NIT/BITS

Roles & Responsibilities:

• Lead AI Product Pods across Credit Risk, Fraud, and Collections functions.

• Build and deploy production-scale Machine Learning systems for lending lifecycle decisioning.

• Own complete ML lifecycle including feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement.

• Design scalable distributed ML infrastructure, feature stores, model registries, and MLOps pipelines.

• Develop AI solutions for underwriting, portfolio risk monitoring, fraud detection, anomaly detection, and recovery optimization.

• Drive model governance, monitoring, explainability, and compliance within BFSI regulatory standards.

• Collaborate with Product, Risk, Engineering, Data, and Business teams to deliver AI-driven business outcomes.

• Define AI platform architecture, operational excellence, SLAs, and incident management practices.

• Build, mentor, and scale high-performing AI Engineering and Data Science teams.

Mandatory Requirements:

• 10+ years of experience in Data Science, AI/ML or AI Engineering with hands-on experience building production-grade ML systems.

• Hands-on experience building AI/ML solutions for Credit Risk, Fraud Risk Management (FRM), Collections & Recovery.

• Current designation must be Lead or above.

• Strong experience designing and deploying large-scale distributed Machine Learning systems.

• Strong programming experience in Python, along with exposure to Spark, Kafka, Kubernetes, APIs/Microservices, CI/CD, Feature Store, Model Registry, and Distributed Computing.

• Experience designing and deploying Credit Risk Models, Fraud Detection Models, Graph ML, Early Warning Systems, Portfolio Monitoring, Collections Optimization, Propensity Models, and Recovery Forecasting.

• Proven experience leading AI/ML teams, owning end-to-end delivery, mentoring engineers, and managing production AI platforms.

• Experience working under BFSI governance, including PII handling, auditability, model governance, compliance, secure-by-design architecture, and model risk management.

• B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are considered.

• Age should be below 37 years.

• CTC breakup: 75% fixed + 25% variable.

Preferred Requirements:

• Currently working as Lead / Principal / Engineering Manager / Associate Director / Director in reputed Product, FinTech, Banking, NBFC, or Global Capability Centers.

• Experience building enterprise AI platforms using Graph ML, Vector Databases, LLM-enabled decisioning, distributed training frameworks, and large-scale AI infrastructure.