Head - Data Science
First seen by Alion on Sep 29, 2026.
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.
Skills
Data Science, Machine Learning, Artificial Intelligence, Data Analytics, Data Scientist, Analytics, Data Modeling