The Head Data & Intelligence Engineering owns the data platforms analytics and AI capabilities that power decision-making and personalized customer experiences at Polaris Bank. This is a leadership role directing four specialist disciplines Data Engineering Analytics & BI Data Science & AI and Data Governance through dedicated leads and engineers not as a hands-on individual contributor across all four.
Key Responsibilities
Data Engineering Oversight
Direct the design of scalable reliable data pipelines warehouses and ETL infrastructure
Set standards for data modeling and infrastructure architecture used across the banks data platforms
Analytics & BI Oversight
Ensure the analytics function delivers dashboards reports and self-service tools that drive data-driven decisions across the bank
Set standards for data visualization and reporting consistency
Data Science & AI Oversight
Direct the development of AI/ML models supporting personalization fraud detection credit scoring and operational optimization
Ensure model performance fairness and reliability are validated before production deployment
Data Governance Oversight
Ensure data quality privacy and metadata management practices are enforced across all data assets
Own the banks data governance framework and ensure regulatory compliance in data handling
Core Competencies
Data platform strategy and technical leadership across engineering analytics and data science
Working fluency in ML/AI model lifecycle management and MLOps practices
Strong grounding in data privacy and regulatory compliance (NDPR and applicable banking data regulations)
Stakeholder management across technology risk and business functions
Familiarity With Tools (used by the functions teams)
Bachelors degree in Computer Science Data Science Statistics or related field; advanced degree an advantage
Demonstrated track record leading data engineering analytics or data science functions ideally in banking or financial services
Required Skills:
. Bachelors degree in Business Marketing Finance or related field; MBA or relevant postgraduate qualification is a plus. Minimum of 5-7 years experience in banking marketing or financial inclusion. Proven track record in developing and scaling customer-focused initiatives preferably targeting women. Strong understanding of gender finance customer segmentation and inclusive banking practices.
About the RoleThe Head Data & Intelligence Engineering owns the data platforms analytics and AI capabilities that power decision-making and personalized customer experiences at Polaris Bank. This is a leadership role directing four specialist disciplines Data Engineering Analytics & BI Data Science...
About the Role
The Head Data & Intelligence Engineering owns the data platforms analytics and AI capabilities that power decision-making and personalized customer experiences at Polaris Bank. This is a leadership role directing four specialist disciplines Data Engineering Analytics & BI Data Science & AI and Data Governance through dedicated leads and engineers not as a hands-on individual contributor across all four.
Key Responsibilities
Data Engineering Oversight
Direct the design of scalable reliable data pipelines warehouses and ETL infrastructure
Set standards for data modeling and infrastructure architecture used across the banks data platforms
Analytics & BI Oversight
Ensure the analytics function delivers dashboards reports and self-service tools that drive data-driven decisions across the bank
Set standards for data visualization and reporting consistency
Data Science & AI Oversight
Direct the development of AI/ML models supporting personalization fraud detection credit scoring and operational optimization
Ensure model performance fairness and reliability are validated before production deployment
Data Governance Oversight
Ensure data quality privacy and metadata management practices are enforced across all data assets
Own the banks data governance framework and ensure regulatory compliance in data handling
Core Competencies
Data platform strategy and technical leadership across engineering analytics and data science
Working fluency in ML/AI model lifecycle management and MLOps practices
Strong grounding in data privacy and regulatory compliance (NDPR and applicable banking data regulations)
Stakeholder management across technology risk and business functions
Familiarity With Tools (used by the functions teams)
Bachelors degree in Computer Science Data Science Statistics or related field; advanced degree an advantage
Demonstrated track record leading data engineering analytics or data science functions ideally in banking or financial services
Required Skills:
. Bachelors degree in Business Marketing Finance or related field; MBA or relevant postgraduate qualification is a plus. Minimum of 5-7 years experience in banking marketing or financial inclusion. Proven track record in developing and scaling customer-focused initiatives preferably targeting women. Strong understanding of gender finance customer segmentation and inclusive banking practices.