Job Purpose: The Manager Human Capital Intelligence leads the development of Human Capital s workforce intelligence capability, transforming governed people data into forward-looking insights that improve workforce, talent, reward, productivity and employee-experience decisions. The role owns the HC intelligence roadmap, analytical standards, HR technology optimisation and responsible use of artificial intelligence, enabling Human Capital and business leaders to make evidence-based decisions aligned with the Bank s strategy, risk appetite and smart-bank ambition. The Manager HC Intelligence acts as Human Capital s accountable business owner and subject-matter partner for workforce data, analytics and AI initiatives. In partnership with the Enterprise AI Unit and relevant control functions, the role defines business requirements, confirms data readiness, supports model validation and adoption, monitors realised benefits and maintains clear accountability for HC decisions arising from analytical or AI-enabled outputs. Key Accountabilities: Develops and executes a prioritised HC Intelligence roadmap aligned with the HC strategy and the Bank s smart-bank ambition, with clear outcomes, milestones, ownership, dependencies, investment needs, adoption measures and realised benefits. Maintains the governed workforce data model and authoritative HC information source, ensuring analytics, dashboards, models and AI use cases meet approved privacy, security, records, ethical and model-governance requirements through defined metrics, lineage, ownership, stewardship, validation, reconciliation, access, change approval and proportionate quality and model-risk controls. Develops and maintains workforce analytics, BI dashboards, scorecards and executive reports covering workforce profile, movement, capacity, talent, learning, succession, engagement, recruitment, mobility, benefits and employee services. Provides evidence-based insights, trends, scenarios and recommendations to the Chief Human Capital Officer and relevant governance forums, clearly distinguishing facts, forecasts, assumptions and limitations. Supports workforce planning with demand and supply analysis, capability gaps, staffing scenarios, productivity indicators and workforce cost projections in partnership with HC Units and business stakeholders. Builds transparent, auditable compensation and benefits models for salary reviews, pay fairness, market benchmarking, promotion and allowance scenarios, benefits optimisation and workforce-cost decisions, aligned with approved reward policy and governance. Improves HRMS adoption, utilisation, data completeness, controls and transaction quality by identifying root causes and coordinating system, process, training and change interventions with HC process owners, Technology and providers. Partners with HC Units and manages relationships with data owners, Technology, Enterprise AI Unit, Finance, Risk, Strategy & Data teams, and external providers to define reporting needs, automate recurring analysis and embed data-driven decisions in HC processes and governance. Manages HC AI and automation use cases from ethical screening and data readiness through requirements, validation, implementation and adoption, coordinating with relevant technical and control functions to ensure human oversight, explainability, monitoring and escalation, and measuring realised value against agreed baselines, benefits measures and post-implementation reviews. Conducts diagnostic, predictive and, where appropriate, prescriptive workforce analysis to identify workforce risks, service bottlenecks, capability requirements and opportunities to improve employee experience and organisational effectiveness, converting findings into prioritised recommendations with clear owners, expected impact and success measures, and monitors agreed actions through relevant HC and management governance forums. Builds data literacy across Human Capital by developing guidance, standard reports and practical capability-building interventions for HC colleagues and relevant managers.

Desired Candidate Profile

Qualifications and Experience: Bachelor's degree in Human Resources, Data Analytics, Artificial Intelligence, Information Systems, Finance or a related discipline. A Master's degree is preferred. Professional certification in People Analytics, Data Analytics, Business Intelligence, HR Systems, Compensation, or Artificial Intelligence is preferred. Minimum of 7 years of progressive experience in people analytics, workforce planning, business intelligence, HR technology, reward analytics or data-led Human Capital transformation, including responsibility for complex analytical initiatives and engagement with senior decision-makers. Experience in banking, financial services or another regulated environment is preferred. Demonstrated proficiency in advanced Excel and at least one enterprise business-intelligence platform, such as Power BI, with practical capability in data modelling, dashboard design and reporting automation. Working knowledge of SQL and statistical or analytical tools such as Python is preferred. Proven experience managing HRMS data, data-quality controls, reporting automation and user-adoption improvement, together with practical experience developing compensation scenarios, workforce-cost models or other quantitative decision-support models, is highly preferred. Excellent written and spoken English and Arabic, with the ability to present analytical findings, governance matters and recommendations clearly to executive, technical and non-technical audiences.