Senior Manager Analytics & AI

Job Title: Senior Manager – AI, Analytics& Data Engineering

Location: Bangalore or Trivandrum

Experience:12–18 years

Education

• MBA / PGDM from a reputed institute
• B.Tech / BE in Computer Science, Information Technology, Engineering, Statistics or related discipline
• AWS Certifications preferred (Solutions Architect, Data Analytics, Machine Learning, AI Practitioner)

About the Role

We are looking for an experienced analytics leader to drive enterprise analytics, AI initiatives, reporting platforms, and data engineering for a leading NBFC. The role combines business strategy, data engineering, machine learning, generative AI, cloud architecture, and stakeholder management to enable data-driven decision making across lending, collections, customer acquisition, risk, finance, and operations.

The ideal candidate should possess strong business acumen along with deep technical expertise in AWS analytics services, AI-assisted development, and modern reporting platforms. The Business understanding till Report delivery

Key Responsibilities

Analytics & Business Intelligence

• Lead enterprise-wide analytics initiatives supporting business growth.
• Build executive dashboards and management reporting.
• Develop analytical frameworks for lending, customer lifecycle, portfolio performance, collections, and profitability.
• Generate actionable business insights through descriptive, diagnostic, predictive, and prescriptive analytics.
• Present findings to senior leadership and business stakeholders.

Data Engineering & AWS

Design and manage enterprise data platforms using AWS technologies including:

• Amazon Redshift
• AWS Glue
• AWS Lambda
• AWS Step Functions

Technical Responsibilities include:

• ETL/ELT pipeline development
• Data warehouse architecture
• Data modelling
• Performance optimisation
• Data quality monitoring
• Metadata management
• Cost optimisation

Artificial Intelligence & Machine Learning

Lead AI initiatives using:

• Amazon SageMaker
• Amazon Bedrock
• Foundation Models
• Retrieval Augmented Generation (RAG)
• Vector Databases
• Prompt Engineering
• Generative AI applications

Develop solutions such as:

• Customer intelligence
• Recommendation engines
• Churn prediction
• Lead scoring
• Document intelligence
• Intelligent assistants
• AI-powered reporting
• Predictive risk models

AI-Assisted Software Development

Champion AI-powered engineering practices using tools such as:

• GitHub Copilot
• Amazon Q Developer, Kiro
• Cursor
• ChatGPT

Responsibilities include:

• AI-assisted coding
• SQL generation
• Code review
• Documentation generation
• Test automation
• Workflow optimisation

Reporting & Visualisation

Develop enterprise reporting using:

• Amazon QuickSight
• Microsoft Power BI
• SQL
• Executive MIS
• KPI dashboards

Ensure:

• Automated reporting
• Self-service analytics
• Near real-time dashboards
• Data governance

Business Analysis

• Gather and document business requirements.
• Translate business problems into analytical solutions.
• Conduct process improvement studies.
• Build business cases for AI and automation projects.
• Work closely with Product, Operations, Risk, Finance, Sales, and Technology teams.

Team Leadership

• Lead and mentor analytics, BI, and data engineering teams.
• Define technical standards and best practices.
• Conduct architecture and code reviews.
• Drive innovation through AI adoption.
• Build analytics capability across the organisation.

Required Technical Skills

Cloud & Data

• AWS
• Redshift
• Glue
• S3
• Lambda
• EC2

AI & ML

• SageMaker
• Amazon Bedrock
• LLMs
• Prompt Engineering
• Machine Learning
• Python
• Scikit-learn
• Pandas

Programming

• SQL (Advanced)
• Python

Reporting

• Amazon QuickSight
• Power BI
• Excel (Advanced)

Databases

• SQL Server
• Redshift

Business Knowledge

Experience in one or more of the following:

• Gold Loans
• Personal Loans
• MSME Lending
• Loan Origination
• Collections
• Risk Analytics
• Customer Analytics
• Branch Performance
• Cross Sell Analytics
• Portfolio Management
• Regulatory Reporting

NBFC or Banking domain experience is preferred.

Leadership Competencies

• Strategic thinking
• Stakeholder management
• People leadership
• Problem solving
• Innovation mindset
• Excellent communication skills
• Project management
• Agile methodologies
• Decision-making under ambiguity

Preferred Experience

• 12–18 years in analytics, BI, or data engineering.
• Experience managing enterprise AWS analytics platforms.
• Proven track record delivering AI and ML solutions in production.
• Experience working with CXOs and business leadership.
• Experience implementing GenAI solutions within financial services.

Success Measures

• Improved business decision-making through analytics.
• Reduced reporting turnaround time.
• Increased automation of reporting and data pipelines.
• Successful deployment of AI/ML solutions into production.
• High adoption of self-service analytics.
• Optimised cloud cost and platform performance.
• Strong stakeholder satisfaction and business impact.

Nice-to-Have Skills

• MLOps
• Data Governance
• Data Catalog
• Apache Airflow
• Docker
• Kubernetes
• CI/CD
• Financial modelling
• Statistical analysis
• NLP
• Computer Vision
• Agentic AI frameworks
• Knowledge Graphs
• Model monitoring
• AI security and responsible AI