D&T Head of Data, BI & Analytics

Head of Data Sciences, Analytics, AI, and BI

innovation, project delivery and steady-state operations

1. Strategic Leadership & Thought Leadership

• Develop and communicate a

  long-term vision and strategy

  for Data Sciences, Analytics, AI, and BI, aligned with Aramex's business strategy and growth objectives.
• Drive

  innovation in analytics and AI

  , exploring emerging technologies, algorithms and methodologies to enhance business decision-making and operational efficiency.

2. Customer & Business Engagement

• Proactively engage business stakeholders to

  understand complex requirements, desired outcomes, and strategic priorities

  .
• Design and deliver

  fit-for-purpose analytics and AI solutions

  that optimize operations, improve customer satisfaction, and drive revenue.
• Use insights from customer feedback, usage analytics, and emerging trends to identify

  continuous improvement opportunities

  .

3. Operational Excellence & Service Delivery

• Own

  end to end operations

  of enterprise analytics platforms, including GCP-based ecosystems (BigQuery, Dataflow, Pub/Sub, Looker) and legacy BI systems (SQL Server, Oracle BI, ETL pipelines).
• Ensure

  platform stability, performance, security and compliance

  through robust ITIL-aligned processes (incident, problem, change, release management).
• Define and maintain

  SLAs, SLOs, and operational KPIs

  for uptime, pipeline reliability, cost efficiency, and user satisfaction.
• Lead

  post-project operationalization

  , including service acceptance, monitoring, and continuous improvement loops.

4. Team Leadership and Capability Development

• Lead and mentor a

  high performing team

  of data scientists, AI engineers, BI analysts, and data operations engineers.
• Build organizational capability in

  analytics, AI, and data engineering

  , fostering a culture of innovation, accountability, and continuous learning.
• Establish team

  KPIs for operational performance, service quality, and business impact

  .

5. Demand Management and Project Oversight

• Oversee

  demand intake, prioritization and resource allocation

  for analytics and AI projects and BAU operations.
• Ensure successful

  Build to Run transitions

  , including operational readiness reviews, documentation, monitoring, access controls, and training.
• Balance

  project delivery with steady-state operations

  , ensuring responsiveness to unplanned business demands while maintaining service stability.
• Partner with Program and Platform leadership to drive

  operational readiness, post go-live support, and continuous improvement

  .

6. Financial and Vendor Management

• Develop and manage

  functional budgets

  aligned with corporate IT and finance guidelines.
• Identify

  revenue generating opportunities

  through data monetization or analytics-as-a-service offerings.
• Optimize

  resource allocation and operational costs

  to maximize ROI on analytics and AI initiatives.
• Manage strategic relationships with

  vendors and managed service providers

  , ensuring SLA compliance, cost-effectiveness, and alignment with business priorities.