Head - Data Science - Fintech/NBFC - IIT/IISc/BITS/NIT/IIIT

ROLE OVERVIEW: The Head of Data Science will serve as the executive technical leader responsible for building, scaling, and operationalizing next-generation data infrastructure, machine learning execution engines, and enterprise AI platform capabilities. This high-impact role brings together Data Engineering, ML Engineering, MLOps, LLMOps / Agentic AI Infrastructure, Enterprise Decisioning Platforms, and SRE / DataOps into a cohesive, production-grade engineering organization. The leader will be accountable for translating business and technology strategy into high-throughput, low-latency, scalable, and audit-ready platform solutions that power real-time credit decisioning, risk modeling, dynamic pricing, fraud prevention, collections, and portfolio management across millions of active accounts. Key Responsibilities: 1. Engineering Leadership: - Build, scale, and mentor Data Engineering, ML Engineering, MLOps, and AI Platform engineering teams while establishing engineering best practices and operational rigor across squads. 2. Enterprise Decisioning Platform: - Design, operationalize, and scale a centralized decisioning platform integrating low-code model development, AutoML, real-time rule engines, policy-as-code, real-time scoring, and automated workflow execution. 3. Data Platform Architecture: - Lead the strategic vision and implementation of scalable, cloud-native Lakehouse architectures using technologies such as Databricks, Delta Lake, Unity Catalog, DLT, and Spark for high-volume batch and real-time streaming workloads. 4. MLOps & LLMOps Standardization: - Establish standardized, production-grade MLOps frameworks along with scalable LLM and Agentic AI infrastructure. 5. Production Deployment & Scaling: - Partner closely with Data Science teams to enable seamless and automated transition of machine learning and deep learning models from experimentation to highly available production environments. 6. Operational Excellence & SRE: - Lead DataOps and SRE functions to ensure high platform availability, proactive automated testing, self-healing systems, and continuous CI / CD delivery. 7. Model & Data Governance: - Operationalize comprehensive model lifecycle governance and regulatory compliance frameworks aligned with applicable financial-services regulations, data-protection requirements, and internal risk policies. 8. Observability & System Health: - Establish end-to-end telemetry and monitoring. Candidate Requirements: - 15 - 22 years of total experience. - 8+ years in senior management - platform leadership. - Only from Top-tier education - IIT / IISc / BITS / NIT / IIIT. - Strong Data Engineering & Data Platform Architecture. - Deep MLOps / ML Platform experience. - AI / LLMOps / Agentic AI infrastructure. - Cloud & Infrastructure - AWS / GCP, Kubernetes, Docker, IaC. - Large-scale engineering leadership. - Fintech / NBFC / Banking + lending / credit / risk / fraud exposure. - Real-time decisioning + production-grade platform experience. - BCA / MCA candidates will not be considered.