Data Scientist Supervisor - Fire

Overview

Position:
Data Analytics Supervisor

Location:

15151 E Alameda Pkwy, Aurora, Colorado Salary: $96,800–$121,000 annually

Application

• Supervise the AFR data and data team.
• Develop, implement, and maintain data governance standards and practices for AFR data systems.
• Analyze fire, EMS, and emergency response data to identify trends, risks, and opportunities for improvement.
• Build predictive models to support call volume forecasting, staffing, and resource deployment.
• Design and maintain dashboards, reports, and performance metrics (e.g., response times, service demand, unit reliability).
• Ensure compliance with reporting standards and regulatory requirements (e.g., NFIRS, NEMSIS).
• Develop and maintain data sources integrating various systems while ensuring data quality, integrity, and standardization.
• Collaborate with internal and external stakeholders, including Fire Operations, EMS, Emergency Management, Members Services, Community Risk Reduction, and City departments.
• Provide data‑driven recommendations to command staff and executive leadership.
• Support command staff with situational awareness tools during high‑demand or major incidents, including activation of the Emergency Operations Center (EOC) as needed.
• Collect, analyze, and present data; cross‑compare and analyze data from Community Operations, Members Services, Community Risk Reduction, and Business Services and present predictive and causative analytics, providing an understanding of department‑wide data.
• Evaluate and implement new technologies and tools to improve analytics capabilities.
• Perform other duties as assigned.

• Education:
  
  Bachelor’s degree in Data Science, Statistics, Computer Science, Public Administration, or related field.
• At least five (5) years of experience in data analysis, data science, business intelligence, or a closely related field, including three (3) years of supervisory experience.
• Experience working with large, complex datasets and multiple data sources.
• Experience developing reports and dashboards for operational and executive audiences.
• Preferred:
  Experience in public safety, fire service, EMS, or emergency management analytics.
• Preferred:
  Master’s degree in a related field.
• Preferred:
  Proficiency with GIS and geospatial analysis tools (e.g., ArcGIS).
• Preferred:
  Experience working with CAD, RMS, or other public safety systems.
• Preferred:
  Experience with predictive analytics and machine learning techniques.
• Knowledge: SQL, Python, R, and data visualization tools (e.g., Power BI, Tableau).
• Knowledge:
  Data governance frameworks, data quality management, and data lifecycle practices.
• Knowledge:
  Statistical analysis, predictive modeling, and data science methodologies.
• Knowledge:
  Data privacy, security, and regulatory compliance requirements.
• Knowledge:
  Performance measurement frameworks and key performance indicators (KPIs) in public safety or government operations.

• Analyze complex data, solve problems, and present findings to varied audiences.
• Data quality assessment and remediation techniques.
• Developing and validating predictive models for forecasting and resource allocation.
• Data visualization and dashboard development using modern BI tools.
• Communicating complex technical information to non‑technical audiences.
• Facilitating cross‑functional collaboration with diverse stakeholders.

• Establish and maintain effective working relationships with diverse stakeholders, including employees, leadership, community members, and elected officials.
• Communicate complex technical information to non‑technical audiences.
• Maintain accuracy and attention to detail in high‑stakes environments.
• Translate operational problems into data‑driven analytical solutions.
• Lead and manage a technical team in a dynamic, mission‑critical environment.
• Evaluate emerging technologies and recommend appropriate tools and systems.

Valid driver’s license or ability to meet the transportation requirements of the position.

• Primarily office environment; occasional off‑site work in noisy, dusty, chemical, or weather‑exposed environments.
• Light…