puestos de It Analyst en United States

JOB PURPOSE

Support the Enterprise Command and Control Departments’ roles related to transportation data analytics and modeling by executing projects and tasks aligned with standards, policies, and procedures. This includes extracting insights from data using advanced analytics and generating reports and dashboards.

KEY RESULTS AND ACCOUNTABILITIES

1. Collaborate with data engineers and analysts to classify, analyze, and integrate data from various sources to create comprehensive transportation datasets, improving analysis accuracy.
2. Incorporate multiple transportation modes into real-time models to analyze intermodal connectivity and develop integrated solutions.
3. Perform transportation modeling tasks such as development, calibration, validation, forecasting, and scenario testing.
4. Conduct sensitivity and uncertainty analyses to evaluate model robustness and identify key influencing factors.
5. Calibrate and validate models by comparing outputs with real-world data to improve accuracy and predictive capabilities.
6. Use KPIs and forecast data from models to generate reports supporting decision-making and journey planning.
7. Perform statistical and spatial data analysis to identify insights related to multi-modal transportation.
8. Develop and update policies and procedures in coordination with stakeholders, ensuring alignment with RTA standards.
9. Design data use cases to address transportation challenges, improve performance, and enhance operational efficiency.
10. Contribute to knowledge sharing and training through workshops and induction programs for new employees.
11. Perform other related duties as required.

Technical Competencies

1. Stakeholder Management
2. Administrative Support
3. Policy Review & Development

Education

Bachelor’s degree in Transportation Engineering, Civil Engineering, Traffic Engineering, or Transportation Planning with at least 5 years of experience in transportation modeling and predictive modeling using machine learning. A Master’s degree or additional qualifications in Computer Science, Applied Math, or Data Science are a plus.

Skills

1. Proficiency with data science tools, machine learning algorithms, data visualization, SQL, NoSQL, and handling large-scale or big data platforms.
2. Knowledge of spatial data analysis using QGIS or GIS software.