01Overview
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Requisition Number: 54409
Job Location: Bangalore, IND
Global Grade: Band 5
Work Type: Office Working
Employment Type: Permanent
Posting Start Date: 01/07/2026
Posting End Date: 21/08/2026
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Job Summary
The Director, Advanced Analytics & AI is a techno-functional leader responsible for designing, building, and industrialising advanced analytics and machine learning solutions that enhance the banks financial risk management, regulatory compliance, and decision-making capabilities.
The role sits at the intersection of:
Business (Risk / Compliance)
CDO (data products)
Technology (engineering & product ionisation)
and ensures an end-to-end lifecycle from use case discovery to production-grade deployment, aligned to regulatory and model governance expectations
Key Responsibilities
Strategy
Lead identification, prioritisation, and shaping of high-impact analytics & ML use cases across Financial Risk and Compliance domains
Translate regulatory and business requirements into analytical problem statements and solution blueprints
Own business value realisation (efficiency, risk reduction, control effectiveness, insights)
Aligns with CoE mandate to drive value-led, outcome-focused AI delivery.
Business
Define end-to-end solution architecture for analytics and ML use cases:
Feature engineering, model selection, evaluation strategy
Data sourcing and transformation requirements
Establish and enforce design patterns, reusable components, and modelling standards
Reflects role of lead architect + capability owner in CoE model
Processes
Personally lead or closely supervise the development of POCs and prototypes for:
New analytical patterns
Complex or regulatory-sensitive use cases
Validate:
feasibility
performance
explainability
Core expectation: prototype validate scale recommendation
Establish reusable:
feature engineering pipelines
model templates
evaluation frameworks
Drive scaling from POCs to enterprise-grade solutions
Critical to avoid one-off analytics and move to repeatable AI products
Define requirements for AI-ready data products with CDO teams:
curated datasets
feature stores
data quality & lineage
Ensure alignment between:
data supply (CDO)
analytics consumption (AI CoE)
Aligns with CoE positioning as bridge between data and intelligence
People & Talent
Lead through example and demonstrate the banks culture and values
Key Responsibilities
Risk Management
Work with Technology and Data Engineering teams to industrialise solutions into production
Provide oversight for:
model integration
pipelines, APIs, and deployment frameworks
Ensure:
functional correctness
alignment to business intent
Consistent with model:
Risk/AI CoE owns logic, validation
Technology owns runtime & engineering
Embed analytics into:
credit risk models
stress testing & forecasting
financial crime detection
regulatory reporting analytics
Ensure outputs are:
explainable
auditable
regulator-ready
Governance
Define and enforce end-to-end model lifecycle controls:
model documentation and explainability
validation frameworks
monitoring (drift, bias, performance)
Ensure compliance with:
Model Risk Management
AI governance, fairness, explainability
Regulatory expectations on AI usage
Strong emphasis on governed lifecycle and audit-readiness
Reporting & Stakeholder Communication
Act as primary interface between business stakeholders, CDO, and Technology
Engage senior stakeholders to:
align priorities
drive adoption
manage regulatory expectations
Role explicitly requires strong business-tech bridging capability
Team Leadership & Capability Building
Lead multidisciplinary teams of:
data scientists
ML engineers
analytics specialists
Coach teams on:
model development best practices
regulatory constraints
production readiness
Build reusable:
frameworks
accelerators
experimentation standards
Key Stakeholders
Data & Analytics
GenAI Specialists
AI Operations
Business Units
Technology (AI Engineering Lead; Data Engineering Lead; platform owners)
Functions CDO stakeholders (standards, platform, data foundations)
AI Services
Legal, Privacy, Cyber Security, Model Risk, Operational Risk
Internal Audit / Assurance partners
COO / Finance partners (capacity and investment planning)
AI Solutions Team
Compliance & Governance
Skills and Experience
Technical and Operational Skills
Strong Hands-On Experience In:
Machine Learning (Classification, Regression .
