The Data & AI Manager is responsible for defining and executing the company's data, analytics, and artificial intelligence agenda to enable data-driven decision-making across investment and corporate functions. Operating within a sovereign wealth fund context, the role focuses on building scalable data platforms, advanced analytics capabilities, and AI use cases that support investment performance, risk management, strategic planning, and operational efficiency, while ensuring strong governance, data quality, and responsible AI use.
Ready to apply for roles like this?
Unlock the company name and direct application link. Subscribers get instant access to fresh jobs across Dubai, Abu Dhabi and Riyadh, many with visa support.
Unlock employer & apply directly
Responsibilities
- Define and lead the company's Data & AI Strategy, ensuring alignment with the Digital Strategy, investment priorities, and corporate strategy.
- Establish enterprise-wide data governance frameworks, including data quality standards, ownership models, and analytics principles.
- Identify, prioritize, and sequence AI and advanced analytics use cases that deliver measurable business value.
- Promote data literacy and adoption across investment and corporate teams to embed data-driven decision-making.
- Act as a strategic partner to senior leadership on data, analytics, and AI-enabled insights.
Core Responsibilities
-
Data Architecture & Analytics Platforms
- Define data and analytics requirements, standards, and target-state architecture in collaboration with IT and enterprise architecture.
- Ensure data and AI solutions meet business requirements for scalability, security, and governance, in coordination with IT.
- Oversee data ingestion, transformation, and modelling to support analytics and reporting needs, with technical data pipeline development and engineering owned by IT.
-
Analytics, AI & Decision Support
- Own the end-to-end AI use-case lifecycle, including identification, prioritization, business case development, value measurement, and adoption.
- Develop dashboards, predictive models, and decision-support tools for investment, strategy, risk, and performance teams.
- Lead the delivery of AI-enabled solutions, including advanced analytics, forecasting, and pattern detection.
- Ensure AI use cases are aligned with business objectives and supported by reliable data foundations.
-
Data Governance & Quality
- Ensure data quality, lineage, consistency, and transparency across enterprise systems.
- Implement data standards, controls, and monitoring mechanisms to support governance and audit requirements.
- Support responsible and ethical use of AI, including transparency, explainability, and appropriate human oversight.
-
Stakeholder Collaboration & Enablement
- Partner with IT and business stakeholders to implement analytics and AI solutions.
- Translate business needs into data and AI requirements and ensure solutions are adopted effectively.
- Support strategic initiatives through advanced analytics and insight generation.
People & Capability Responsibilities
- Build and develop data and analytics capabilities across teams.
- Establish knowledge-sharing practices, standards, and best practices for analytics and AI adoption.
- Support capability uplift through training, tools, and data literacy initiatives.
Key Deliverables
- Enterprise data platforms and standardized analytics dashboards.
- AI use cases supporting investment research, risk analysis, performance measurement, and strategic planning.
- Data governance frameworks, policies, and standards.
- Insight-driven support for strategic and investment initiatives.
Requirements
Education & Qualifications
- Bachelor’s or master’s degree in data science, Computer Science, Engineering, Statistics, or a related field.
Experience Requirements
- 8–12 years of experience in data, analytics, or AI roles within complex organizations.
- Experience within sovereign wealth funds, asset owners, or investment managers strongly preferred.
- Proven experience delivering enterprise analytics platforms and AI-driven solutions.
- Strong understanding of data platforms, cloud-based analytics, and machine learning concepts.
Technical Expertise / Skills / Knowledge
- Data architecture, analytics platforms, and reporting tools.
- AI and machine learning concepts and practical applications.
- Data governance, quality management, and metadata practices.
- Cloud-based data ecosystems and modern analytics stacks.
- Strong ability to translate complex data insights into business-relevant outcomes.
- Excellent stakeholder engagement and communication skills.
