Closing Date 2025-03-22
Job Description
Key Objectives:
- Develop and implement a comprehensive enterprise-wide data and AI strategy aligned with the bank's overall business objectives.
- Build and lead a world-class data science and AI team, attracting, retaining, and developing top talent.
- Establish a robust data governance framework and infrastructure to ensure data quality, security, and compliance.
- Drive the adoption of AI and machine learning across all business lines, including retail banking, wealth management, investment banking, risk management, and overall internal operational efficiencies.
- Drive AI-powered digital transformation initiatives across banking products, services, and operations to enhance customer experience, improve operational efficiency, and generate new revenue streams.
- Foster a data-driven culture within the organization, empowering employees with data insights and tools.
- Collaborate with technology teams to ensure seamless integration of data and AI solutions into existing systems.
- Stay abreast of the latest advancements in AI and data science and proactively identify opportunities for innovation.
Roles and Responsibilities:
- Strategy & Vision - Define and execute the bank's data and AI vision, roadmap, and strategic priorities.
- AI and Data Strategy Development & Execution - Define and implement the bank’s AI and data strategy, ensuring alignment with overall business objectives.
- Drive AI-powered digital transformation initiatives across banking products, services, and operations.
- Identify new revenue streams and operational efficiencies through AI, machine learning (ML), and advanced analytics.
- Collaborate with business leaders to identify opportunities for AI and data-driven solutions to improve customer experiences and operational efficiencies.
- Champion AI and data initiatives, ensuring they provide measurable business value and competitive differentiation.
- Foster a data-driven culture, enabling teams to make informed, evidence-based decisions.
- Establish and enforce enterprise-wide data governance frameworks, policies, and best practices and standards.
- Ensure compliance with regulatory requirements (e.g., GDPR, Basel, local banking regulations) related to AI, data privacy, and security.
- Develop risk mitigation strategies to manage AI biases, ethical concerns, and operational risks.
- Oversee the development and maintenance of a robust data and AI infrastructure.
- Lead the adoption and implementation of AI/ML platforms, data lakes, and analytics tools.
- Oversee the integration of AI-powered solutions with core banking systems and digital channels.
- Drive cloud-based and on-premises data modernization initiatives to support real-time analytics and decision-making.
- Build, manage, and mentor a high-performing team of data scientists, engineers, and analysts, attracting and retaining top talent.
- Partner with HR and business units to develop AI literacy and upskilling programs across the bank.
- Build, manage, and mentor a high-performing team of data scientists, engineers, and analysts.
- Foster an innovation-driven, agile culture within the bank’s AI and data functions.
- Vendor Management - Manage relationships with external data and AI vendors.
- Oversee the budget for data and AI initiatives.
- Communicate the value of data and AI to stakeholders across the organization, position the bank at the top of the industry on its innovation and value to the stakeholders.
Key Performance Indicators (KPIs):
- Business Impact - Increased revenue, reduced costs, improved customer satisfaction, and enhanced operational efficiency attributable to data and AI initiatives.
- Data Quality - Improved data accuracy, completeness, and consistency.
- AI Adoption - Number of AI solutions deployed across the bank and their utilization rates.
- Team Performance - Team growth, employee satisfaction, and retention rates.
- Innovation - Number of new data-driven products and services launched.
- Compliance - Adherence to data governance policies and regulatory requirements.
- Return on Investment (ROI) - Measurable return on investment for data and AI projects.
Requirements
- Advanced degree (Master's or Ph.D.) in Computer Science, Data Science, Statistics, or a related field.
- Extensive experience (10+ years) in IT, data science, CXO position in technology, with a proven track record of leading and delivering successful data and IT initiatives.
- Deep understanding of machine learning algorithms, statistical modeling, and data visualization techniques.
- Strong knowledge of data governance, security, and compliance regulations.
- Experience in the financial services industry is highly preferred.
- Excellent leadership, communication, and interpersonal skills.
- Ability to influence and collaborate with senior executives and business stakeholders.
- Strong analytical and problem-solving skills.
- Passion for data and AI and its potential to transform the banking industry.
