Data Science Senior Manager

About the Company:

Red Sea Gateway Terminal International is a leading group in the ports and terminals sector, committed to driving operational excellence, innovation, and sustainable growth. As part of our ongoing expansion and focus on robust governance, we are seeking a Data Science Senior Managerwith specialized experience in container and multi-purpose port operations.

Purpose of the Job:

The Data Science Senior Manager is Responsible for Leading RSGT's enterprise-wide data science capability to transform the way the business uses data and advanced analytics for decision-making, operational optimization, and strategic growth. Developing predictive, prescriptive, and cognitive analytics models that drive measurable business value in port operations, asset management, logistics efficiency, safety, and customer experience. Will be a key enabler of RSGT's AI and Digital Transformation Strategy, ensuring data-driven insights are embedded in all levels of the organization.

Key Responsibilities:

1- Strategy & Leadership:

• Support development and own execution of RSGT's Data Science and Advanced Analytics Strategy aligned with corporate and AI transformation objectives.
• Establish the vision, roadmap, and governance framework for leveraging data science across the terminal and group operations.
• Lead the Data Science Centre of Excellence (CoE), fostering collaboration between operations, IT, engineering, finance, commercial, and safety functions.
• Champion a culture of data-driven decision making, ensuring adoption of AI/ML solutions by business units.
• Partner with the IT and Digital teams to embed AI-enabled optimization into core port and logistics processes.

2- Analytics & Model Development:

- Design and oversee development of predictive and prescriptive models for key business domains such as:

1. Vessel and berth optimization (ETA prediction, berth planning, quay crane scheduling)
2. Terminal Yard and container flow optimization
3. Equipment maintenance (predictive maintenance for cranes, trucks, reach stackers)
4. Safety and risk analytics (incident prediction, near-miss detection, CCTV image analytics)
5. Commercial and finance analytics (pricing, demand forecasting, cost optimization)
6. Sustainability analytics (energy usage, carbon footprint modelling, emissions prediction)

• Lead R&D on use of AI, machine learning, computer vision, and natural language processing for terminal and logistics applications.
• Ensure development and deployment of MLOps pipelines for model lifecycle management, monitoring, and scalability.

3- Data Governance & Architecture:

• Work closely with the Data Engineering and IT teams to define data architecture standards, ensuring high-quality, secure, and accessible data.
• Contribute to RSGT's Data Governance Framework, covering data ownership, metadata, lineage, and data quality controls.
• Define and enforce data ethics and AI governance principles consistent with regulatory and ethical standards.
• Partner with cybersecurity to ensure protection of operational, customer, and partner data.

4- Capability Building & Change Management:

• Build and lead a high-performing Data Science team, recruiting top talent in data engineering, AI, and analytics.
• Develop skill-building programs and partnerships with universities, AI institutes, and port technology providers.
• Conduct workshops and training to improve data literacy and AI adoption across business functions.
• Promote cross-functional collaboration and communicate data science impact stories to leadership and the broader organization.

5- Performance & Value Realization:

• Define measurable success metrics (ROI, efficiency gain, cost savings, throughput optimization, etc.) for every data science initiative.
• Track and report on business value realized from data-driven initiatives.
• Establish dashboards and insights platforms to communicate results to executive leadership.
• Continuously assess emerging technologies and methods to keep RSGT at the forefront of AI-driven innovation in the port industry.

Skills & Qualifications:

• Master's or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or related field.
• Certification or coursework in Machine Learning / AI / Advanced Analytics (preferred).
• 10+ years of experience in data science, analytics, or AI, including at least 5 years in a data leadership role, with a strong record of delivering impactful AI/ML projects.
• Data-Driven Decision Making
• Analytical Thinking
• Results Orientation
• Collaboration & Influence
• Problem Solving
• Innovation
• Customer Centric
• Integrity
• Dynamic