Data Science and Business Intelligence Manager

Role Summary

The Data science & BI Manager will lead the bank's data analytics, reporting strategy, data governance, and BI platform development. The role ensures the accuracy, quality, and availability of data for business decisions, regulatory reporting, and strategic initiatives. The manager will oversee data extraction, transformation, visualization, and data governance processes to support audit readiness, regulatory compliance, and business growth.

Key Responsibilities

1. Data Analytics & BI Strategy

• Lead the design and execution of the bank's BI and analytics strategy.
• Oversee development of dashboards, reports, and analytical models for business units.
• Enhance data visualization and advanced analytics capabilities using modern BI tools.
• Support senior management with data-driven insights for strategic decision-making.

2. Data Governance & Quality Assurance

• Implement and maintain data governance framework, policies, and data standards.
• Ensure data quality, consistency, accuracy, and integrity across all systems.
• Oversee master data management (MDM), data dictionaries, and business glossaries.
• Work with IT, Risk, Compliance, and business units to ensure data controls are effective.

3. Audit Readiness & Regulatory Compliance

• Ensure the Data & BI function is always audit-ready, including documentation, processes, and data evidence.
• Support internal and external audits for data accuracy, controls, lineage, and reporting.
• Ensure compliance with QCB (Qatar Central Bank) reporting requirements and data guidelines.
• Maintain evidence repositories for regulatory inspections and data governance audits.

4. Data Architecture & ETL/ELT Management

• Oversee the design and maintenance of data warehouses, data lakes, and data pipelines.
• Manage ETL/ELT workflows to ensure reliable data movement and transformation.
• Ensure alignment between data architecture and business needs.

5. Reporting & Business Support

• Develop automated and standardized MIS and regulatory reporting across the bank.
• Collaborate with business units to provide insights on customer behavior, credit risk, operational performance, and financial trends.
• Reduce reliance on manual reporting through automation and optimized data pipelines.

6. Advanced Analytics, AI & Innovation

• Lead the development and deployment of advanced analytics solutions, including predictive modeling, machine learning (ML), and artificial intelligence (AI) applications.
• Identify high-impact use cases for AI/ML across banking functions such as credit scoring, fraud detection, customer segmentation, and operational efficiency.
• Oversee the lifecycle of AI/ML modelsfrom data preparation and model training to validation, deployment, and monitoring.
• Collaborate with data scientists, engineers, and business stakeholders to ensure AI/ML solutions align with strategic objectives and regulatory expectations.
• Establish model governance practices, including model documentation, explainability, fairness, and performance tracking.
• Evaluate and adopt emerging AI/ML technologies, frameworks, and platforms to enhance analytical capabilities.
• Promote responsible AI practices, ensuring ethical use of data and compliance with data privacy regulations.

7. Team Leadership & Stakeholder Management

• Lead and mentor the Data & BI team (analysts, data engineers, BI developers).
• Manage workload, priorities, and performance of the team.
• Act as a key point of contact for data-related initiatives across the organization.

Required Qualifications

• Bachelor's degree in:

-Data Science

-Computer Science

-Information Systems

-Statistics

-Engineering

-or related field

• Master's degree is an advantage.
• Relevant certifications preferred:
• Microsoft Power BI / Tableau / Qlik certifications
• Data governance certifications (e.g., DCAM)
• Google Cloud / Azure Data specialty certifications
• SQL or data engineering certifications

Experience Requirements

• 812 years total experience in Data, BI, Analytics, or Data Engineering.
• At least 5+ years of experience in a managerial or senior specialist role.
• Experience in banking or financial services is mandatory or strongly preferred.
• Hands-on experience with:
• Data warehouse / data lake platforms
• BI tools (Power BI, Tableau, Qlik, etc.)
• SQL, Python, R
• ETL/ELT tools
• Regulatory and MIS reporting
• AI and Machine Learning.
• Experience preparing data teams for audits and regulatory inspections.

Skills & Competencies

• Strong analytical and data interpretation skills.
• Excellent knowledge of SQL, data modeling, and BI visualization.
• Understanding of banking data structures such as:
• Customer data
• Credit/Risk data
• Financial and operational metrics
• Strong documentation and reporting skills.
• Ability to maintain a state of continuous audit and regulatory readiness.
• Excellent communication, stakeholder management, and leadership skills.
• High attention to detail, data accuracy, and integrity.