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The Head of Data Sciences, Analytics, AI, and BI is a senior strategic and operational leader within Aramex’s Digital & Technology organization. This role spans thought leadership, strategic planning, capability building and operational excellence across the BI, analytics and AI landscape. This role balances innovation, project delivery and steady-state operations, ensuring the end-to-end reliability, scalability, and operational performance of Aramex’s analytics platforms.
Job Responsibility:
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.
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.
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.
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.
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.
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.
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