Data Management / Analytics Expert

Parsons Corporation


Date: 14 hours ago
City: Riyadh
Contract type: Full time
In a world of possibilities, pursue one with endless opportunities. Imagine Next!

When it comes to what you want in your career, if you can imagine it, you can do it at Parsons. Imagine a career working with intelligent, diverse people sharing a common quest. Imagine a workplace where you can be yourself. Where you can thrive. Where you can find your next, right now. We’ve got what you’re looking for.

Job Description

Parsons is seeking a highly skilled and experienced Data Management / Analytics Expert to join our transportation technology team on a high-profile project in Saudi Arabia. This role is pivotal in leveraging big data to drive insights and optimizations for traffic management systems, enabling data-driven decision-making in large-scale urban transportation projects. The ideal candidate will have deep expertise in transportation data analytics, big data processing, visualization tools, and statistical analysis to support scalable solutions for traffic optimization.

What You'll Be Doing

  • Design and implement data management strategies for transportation datasets, including ingestion, processing, and storage of traffic, sensor, and mobility data from diverse sources (e.g., ITS systems, APIs, sensors).
  • Develop advanced analytics workflows to process big data, applying statistical models and machine learning techniques to derive insights for traffic flow, congestion prediction, and optimization.
  • Build and maintain visualization dashboards and tools (e.g., using Tableau, Power BI) to present complex transportation data in actionable formats for stakeholders.
  • Implement data-driven solutions for traffic optimization, such as real-time analytics for adaptive signal control, predictive modeling for demand management, and performance evaluation of transportation systems.
  • Ensure data quality, reliability, and compliance through validation frameworks, anomaly detection, and integration with transportation-specific standards.
  • Collaborate with traffic engineers, ITS specialists, and project stakeholders to translate data insights into operational improvements and policy recommendations.
  • Mentor team members on analytics best practices and contribute to continuous improvement in data handling and analysis methodologies.


What Required Skills You'll Bring

  • Bachelor's or Master’s degree in Data Science, Computer Science, Transportation Engineering, or a related field.
  • 10+ years of experience in transportation data analytics, data management, or related fields.
  • Expertise in big data processing technologies (e.g., Hadoop, Spark) and visualization tools (e.g., Tableau, Power BI).
  • Proficiency in statistical analysis, Python/R for data modeling, and SQL for querying large datasets.
  • Experience implementing data-driven traffic optimization solutions, including predictive analytics and simulation-based insights.
  • Strong problem-solving skills and ability to work independently in a fast-paced environment.


What Desired Skills You'll Bring

  • Experience with transportation-specific tools (e.g., SYNCHRO, VISSIM for traffic simulation integration) and real-time data processing (e.g., Kafka, Spark Streaming).
  • Familiarity with data governance, security, and compliance in public sector transportation projects.
  • Certifications in data analytics (e.g., Google Data Analytics, Microsoft Certified: Azure Data Scientist) or transportation-related fields.


Parsons equally employs representation at all job levels no matter the race, color, religion, sex (including pregnancy), national origin, age, disability or genetic information.

We truly invest and care about our employee’s wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest—APPLY TODAY!

Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer to https://www.parsons.com/fraudulent-recruitment/.

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