محلل بيانات

About the Role

AtkinsRéalis is seeking an experienced Data Analyst to support data-driven decision-making within public transportation systems in Medina, Al Madinah. This full-time role focuses on analyzing fare collection data, passenger behavior, revenue performance, and system efficiency, requiring a strong understanding of transportation operations.

Key Responsibilities

• Analyze AFC transaction data (smart cards, mobile tickets, contactless payments) to identify trends in ridership, revenue, and passenger flow.
• Develop dashboards and reports tracking KPIs such as ridership, fare evasion, peak usage, and revenue leakage.
• Perform data validation and quality checks to ensure the integrity of AFC datasets.
• Provide insights into passenger travel patterns, route performance, and network utilization.
• Support planning teams with demand forecasting and capacity planning.
• Analyze multimodal integration (bus, metro, tram) using AFC data.
• Build predictive models for ridership forecasting, fare optimization, and demand analysis.
• Apply statistical techniques and machine learning where applicable.
• Conduct scenario analysis to support policy or fare structure changes.
• Work with AFC system vendors and internal IT teams to manage data pipelines and integrations.
• Extract, transform, and load (ETL) large datasets from AFC systems and data warehouses.
• Ensure compliance with data governance and security standards.
• Collaborate with operations, finance, and planning teams to translate data into actionable insights.
• Present findings and recommendations to senior stakeholders and leadership.
• Support audits and regulatory reporting requirements.

Qualifications and Experience

• Bachelor's degree in Data Science, Statistics, Computer Science, Transportation Engineering, or a related field. A Master's degree is preferred.
• Over 10 years of experience in data analysis, ideally within public transportation or mobility sectors.
• Proven experience working with AFC systems (*, Cubic, Thales, Scheidt & Bachmann).

Technical Skills

• Strong proficiency in:

  • SQL (advanced level).
  • Python or R for data analysis.
  • Data visualization tools (Power BI, Tableau).

• Experience with:

  • Big data platforms (*, Hadoop, Spark) is a plus.
  • GIS tools (ArcGIS/QGIS) for spatial analysis.
  • ETL tools and data warehousing concepts.

Domain Knowledge and Soft Skills

• Strong understanding of:

  • Public transportation operations.
  • Fare structures and ticketing systems.
  • Transit KPIs and performance metrics.

• Soft Skills:

  • Strong analytical and problem-solving skills.
  • Excellent communication and data storytelling abilities.
  • Ability to work cross-functionally in complex environments.

Preferred Qualifications

• Experience in smart mobility or digital ticketing transformation projects.
• Knowledge of contactless EMV payment systems.
• Familiarity with real-time data analytics in transportation.
• Experience in large-scale metro, rail, or bus network environments.