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bayt

Transport Data Science Manager

Unknown
Riyadh Region, KSA
Part-time
Onsite
Discovered Yesterday
Transport data scienceTransport data engineeringArtificial intelligence and machine learningPredictive modelingCloud data and AI architecturesData governance
Free

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Transport data scienceTransport data engineeringArtificial intelligence and machine learning
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Opportunity overview

This opportunity is for a bid and is not yet a secured role.

The project is a major mixed-use development in Saudi Arabia with sports, entertainment, arts, and associated infrastructure.

The role will lead data-driven intelligence across a transport and mobility ecosystem.

Responsibilities

  • Lead integrated transport data strategies across mobility modes, defining use cases, KPIs, and performance frameworks.
  • Deliver predictive models and AI solutions for demand, ridership, fleet optimization, traffic management, safety, and customer insights.
  • Enable scalable cloud-based data and AI architectures with integration to autonomous vehicle and MaaS platforms.
  • Establish data governance and knowledge management frameworks for quality, compliance, traceability, and lifecycle management.
  • Collaborate with technology vendors, autonomous vehicle providers, system integrators, and internal stakeholders.
  • Support proactive identification and management of carbon emissions and reductions during delivery.

Required qualifications

  • Bachelor’s degree in data science, data engineering, AI/machine learning, transport systems engineering, or a related discipline.
  • At least 8 years of experience in transport data engineering and AI/ML.
  • Experience working on high-value projects or programmes for a project management consultancy business.

Preferred qualifications

  • GCC experience is highly regarded.

Work arrangements

  • Part-time, flexible, and hybrid working options may be discussed if suitable for the role.

Employer values

The employer emphasizes safety, client focus, integrity, opportunity, continuous improvement, and inclusive collaboration.

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