Research and Data Analyst (MAII)
Summary
Data Analytics Specialist with Edmonton Transit Service leading complex analytical projects across the public transit network. Builds ETL pipelines in SQL and Python, develops machine learning models, and creates interactive Tableau dashboards to inform strategic and operational decisions.
Driven by data and passionate about shaping the future of public transit? Edmonton Transit Service (ETS) is seeking a skilled and innovative Data Analytics Specialist to help guide strategic decisions across our transit network! In this role, you will lead complex analytical projects, build robust data pipelines, and craft dynamic dashboards that directly inform leadership and operational strategies. You will work closely with collaborators across the organization to uncover actionable insights, streamline processes, and drive continuous improvement. If you thrive on converting complex, large-scale datasets into smart operational solutions, this is your opportunity to make a tangible impact on our city's public transit system.
The Data Analytics Specialist performs advanced professional analytics to support transit planning, ridership, and operational efficiency across ETS. This position leads data engineering, automation, and predictive modeling efforts to convert raw operational data into actionable insights for branch leadership. Responsible for developing custom ETL workflows, machine learning models, and interactive visualization tools, the role directly supports data-driven decision-making and strategic planning. Additionally, this role manages key analytical reporting for grant programs, industry benchmarking, and corporate decision-making. Operating with a high degree of independence, the specialist addresses complex operational challenges where established solutions may not yet exist.
What will you do?
- Lead the end-to-end Extract, Transform, and Load (ETL) processes from raw data to actionable business insights
- Write custom scripts in SQL and Python to build automated data pipelines and predictive models
- Design and build interactive dashboards and reports using Tableau and other visualization tools to track operational KPIs
- Analyze complex transit data—including ridership, on-time performance, and schedule adherence—to identify operational trends and recommend efficiency improvements
- Develop predictive, statistical, and behavioral models using supervised and unsupervised machine learning techniques
- Collaborate with IT teams to transition prototype analytical models into production-level solutions
- Prepare data products, briefings, and technical research support for Council reports and executive presentations
- Ensure data integrity and quality standards across multiple transit data systems while advancing open data initiatives