Head of Data Analytics & AI

1. Data, Analytics & AI Strategy
- Define and drive the enterprise-wide Data Analytics & AI strategy aligned with overall business objectives.
- Promote and embed a data-driven culture across all levels of the organization.
- Identify and prioritize opportunities to apply Advanced Analytics and AI to generate business value, operational efficiency, and competitive advantage.
- Oversee the design, implementation, and governance of enterprise data platforms, including data lakes, data warehouses, and analytics tools.
2. Data Platform & Analytics Enablement
- Lead the development of dashboards, management reporting, and self-service analytics capabilities.
- Ensure data quality, integrity, and compliance with applicable regulations (e.g., GDPR, local banking and financial regulations).
3. AI/ML & Advanced Analytics
- Lead the research, development, and deployment of machine learning models, natural language processing, computer vision, and other AI techniques.
- Partner with business functions (e.g., Risk, Credit Scoring, Customer Engagement, Fraud Detection, Operations) to design and implement AI-driven use cases.
- Build and scale MLOps capabilities to ensure robust model lifecycle management, monitoring, and continuous improvement.
4. People, Stakeholder & Vendor Management
- Lead, mentor, and develop high-performing teams of Data Scientists, Data Engineers, and Analysts.
- Collaborate closely with the CIO and senior business leaders to translate business challenges into scalable Data & AI solutions.
- Manage vendor relationships and evaluate emerging technologies, tools, and strategic partnerships.
5. Governance, Risk & Compliance
- Establish and maintain data governance and AI governance frameworks, ensuring ethical and responsible AI practices.
- Ensure compliance with data security, privacy, and data usage regulations.
- Identify and manage risks related to AI adoption, including model bias, explainability, and accountability.
6. Other tasks as assigned by the manager.

1. Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field; PhD is preferred.
2. Experience: 
- Minimum 8 years of experience in data, analytics, or AI roles, with at least 5 years in leadership or management positions.
- Proven experience leading AI/ML initiatives in a business environment, preferably within financial services, fintech, or consumer-focused industries.
- Demonstrated track record of delivering measurable business impact through analytics- and AI-driven solutions.
3. Skills & Professional Competencies: 
- Strong expertise in big data platforms, cloud technologies (AWS, Azure, GCP), and modern data architectures.
- In-depth knowledge of data governance, AI ethics, and regulatory compliance requirements.
- Excellent leadership, stakeholder management, and communication skills.