Role Purpose:

The Head of Data & AI will be the enterprise leader responsible for defining and executing the firm's Data & AI strategy, architecture, platforms, governance and capabilities.

The role will establish Data & AI as a strategic enterprise capability for the firm and its cooperative banking ecosystem, covering the full lifecycle from data acquisition and engineering to data products, analytics, machine learning, Generative AI and Agentic AI.

Primary Job Responsibilities:

1. Enterprise Data & AI Strategy:

- Define and own the firm's multi-year Enterprise Data & AI Strategy, aligned with the organisations product, technology and business strategy.

- Establish the target-state architecture and roadmap covering data platforms, analytics, AI/ML, Generative AI and Agentic AI.

- Identify and prioritise strategic Data & AI capabilities and use cases based on business value, feasibility, risk and ecosystem impact.

2. Enterprise Data Platform & Architecture:

- Own the architecture and evolution of the firm's enterprise data platform / lakehouse and associated data services.

- Establish standards for batch and real-time data ingestion, data modelling, data integration, APIs, data contracts, metadata, lineage and interoperability.

3. Data Governance & Data Management:

- Establish and institutionalise the enterprise Data Governance Framework, including ownership, stewardship, classification, quality, lineage, metadata and access controls.

4. AI, Machine Learning & Agentic AI:

- Define the firm's enterprise AI strategy covering traditional ML, Generative AI and Agentic AI.

- Establish reusable AI capabilities, platforms, model services, evaluation frameworks and deployment patterns.

5. AI & Model Governance:

- Establish the enterprise AI and model governance framework covering the complete model lifecycle.

6. AI Trust, Security & Responsible AI:

- Establish an enterprise framework for trusted and responsible AI covering explainability, transparency, traceability, human oversight, fairness, security and accountability.

7. Fraud, Risk & Financial Intelligence:

- Own enterprise-level data and AI capabilities supporting fraud risk management and transaction monitoring.

8. Data & AI Products and Business Outcomes:

- Partner with Product, Business, Risk, Compliance and Technology leadership to translate institutional priorities into a prioritised portfolio of Data & AI products and use cases.

9. Ecosystem & Interoperability:

- Define standards for integrating the firm's Data & AI capabilities with core banking systems, external platforms, ecosystem partners and Indias digital public infrastructure.

10. Leadership & Capability Building:

- Build and lead a high-performing Data & AI organisation spanning Data Engineering, Platform Engineering, Analytics, Data Science, ML/AI Engineering, AI Product Management and Governance.

11. Vendor & Delivery Governance:

- Own governance of strategic Data & AI technology partners, systems integrators and specialist vendors.

12. Regulatory, Audit & Board Engagement:

- Act as the senior enterprise point of accountability for Data & AI matters with regulators, supervisory bodies, auditors and internal governance forums.

Professional Skills & Experience:

- 1215+ years of experience in Data, Analytics, AI/ML or technology leadership, with significant experience leading enterprise-scale Data & AI functions.

- Proven experience building a Data & AI organisation, platform or capability from the ground up.

- Strong experience in banking, financial services, fintech, payments, insurance or another highly regulated environment.

Preferred Technical Exposure:

- Modern data lakehouse / data platform architectures

- Cloud and hybrid-cloud data platforms

- Streaming and event-driven data architectures

- Machine Learning platforms and MLOps

- Generative AI and LLM architectures

- Agentic AI and multi-agent orchestration

- AI governance and responsible AI

Educational Qualifications:

- B.Tech / B.E. / MCA / Masters degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Engineering or an equivalent discipline.

- A postgraduate qualification in management, technology or a related discipline is desirable.