About the Role The Aviation Department is seeking a Senior Data Scientist with strong analytical skills, a passion for civic tech, excellent technical judgment, GIS experience, and the ability to collaborate across diverse business units. The ideal candidate will be motivated to strengthen the Department’s data-driven mindset and analytical capabilities, expand the reach of the Aviation Data Analytics Warehouse (ADAW), and develop data-driven tools that support operational decisions across our airports. The Data Analytics & Business Intelligence (DABI) team serves as the centralized analytics and data science unit for the Department and manages ADAW, a governed data environment integrating more than fifteen data streams and supporting more than 500 users across the agency. Reporting to the Program Manager, Data Analytics & Business Intelligence, the Senior Data Scientist will work in tandem with the Senior Data Engineer to support the development, enhancement, and maintenance of data products and analytical workflows; lead predictive and diagnostic modeling efforts; develop and maintain operational dashboards; support new data integrations; and partner with business units to translate complex needs into sustainable and actionable data-driven solutions. This role is a critical contributor to the decision-support systems that move millions through our world-class airport system. The successful candidate’s responsibilities will include, but are not limited to: Operational Dashboards, Reporting & Predictive Modeling (50% of your portfolio) - Develop, maintain, and enhance Power BI dashboards that support Central Office business units, Airport Operation Centers (AOCs) staff, planning partners, and customer experience teams.
- Create predictive models, structured analyses, real-time awareness dashboards, and forecasting tools that support resource planning, real-time operational monitoring, performance insights, anomaly detection, and other emerging operational needs.
- Document dataset structures, logic, modeling assumptions, and processing steps to ensure clarity, transparency, and long-term sustainability.
Product Development & Technical Solutioning (20% of portfolio) - Build custom analytical solutions — including Python-based tools, KPI reporting engines, interactive dashboards, and data-entry workflows — to help operational and strategic partners understand operational conditions, identify trends, and make informed decisions.
- Build and maintain automated processes via Power Automate, Synapse pipelines, Azure Function Apps, Databricks jobs, or Python scripts—to streamline reporting, monitoring, and dataset preparation.
- Lead GIS Integration into current data architecture and workflows, responsible for coordinating with relevant agency-wide teams such as Planning, Asset Management, Central Survey, and Engineering to utilize and maintain spatial assets.
- Explore and pilot advanced analytics, aligning with Program Manager on which innovations should advance towards production.
Cross-Department Collaboration & Stakeholder Engagement (15% of portfolio) - Engage directly with business units, airport operations teams, and external partners to gather requirements, refine analytical products, and align on business rules and technical expectations.
- Participate in recurring technical discussions, coordination meetings, and cross-team. collaborations to ensure ADAW analytics remain consistent, reliable, and responsive to evolving departmental needs.
- Communicate analytical considerations clearly to nontechnical stakeholders, helping them understand data limitations, opportunities, and implications.
- Provide technical guidance to colleagues across the department, including embedded analysts, to strengthen analytics, modeling, and workflow development capacity.
- Support collaborative efforts with units such as Airport Operation Centers, Traffic Engineering, Redevelopment, and Central Office teams to ensure alignment in assumptions, logic, and analytic practices.
Data Integration, Access Management & Workflow Development (15% of portfolio) - Partner with the Data Engineer to support the design, development of new aviation data streams as well as enhancement of ADAW’s existing analytical workflows, including batch and real-time Python- and PySpark-based processes in Azure Synapse and Databricks.
- Own frontend user permissioning and oversee proper Power BI workspace governance, including workspace roles, access control, audience configuration, and App permissions.
- Contribute to internal best practices for analytical workflow design, governance standards, documentation, reproducibility, and sustainable architecture.
Minimum Qualifications - Bachelor’s degree in Data Science, Urban Planning, Transportation Planning, Computer Science, Information Systems, Applied Mathematics, Engineering, or a related quantitative field.
- At least three (3) years of experience in an analytical role supporting data systems, analytics workflows, or data science activities in an enterprise environment (ideally Azure).
- At least two (2) years of experience working in, or partnering with, large organizations, public service agencies, regional transportation bodies, or civic tech organizations, ideally in an analytical or data-oriented capacity.
- Strong proficiency with Python and SQL, including experience building analytical workflows, automating tasks, and working with cloud-hosted datasets.
- Experience with PySpark or distributed data processing in platforms such as Databricks or Azure Synapse.
- Experience designing or supporting structured analytical solutions or operational dashboards for cross-functional teams, ideally in a large organization or public sector environment.
- Ability to multitask, prioritize, and manage time effectively.
- Strong written and verbal communication skills and the ability to work collaboratively with technical and nontechnical partners across the Department.
Desired Qualifications - Master’s degree in a relevant analytical or technical field (Data Science, Engineering, Information Systems, Statistics, Computer Science).
- Experience with operational datasets in transportation, infrastructure, or other complex, high-volume environments.
- Experience with API development, ingestion workflows, or automated data transfer protocols.
- Familiarity with enterprise GIS systems and geospatial data management or experience contributing to map-based or spatially-aware analytics
- Experience with real-time data ingestion and processing workflows, especially in Azure Event Hubs or similar Azure-compatible cloud-based platform
- Knowledge of building agentic AI workflows and integrating AI agents into cross-functional analytical tools
- Experience improving data quality, governance, documentation, or `analytic processes within a collaborative team environment.
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