AWSCloudPandasPythonRemote SensingRStatistical AnalysisParcelAmazon Web ServicesGitHubVersion ControlLeadershipPrototypingCommunicationCollaboration
About this role
Role Overview
Analyzes spatial and statistical data
Implements test and validation protocols
Contributes to written reports supporting the research of the Fire Safety Research Institute (FSRI) and fire risk and resilience science.
Works closely with other FSRI leaders and researchers in contributing to applied mathematical models, visualizing spatial analytic outputs and products, and other information dissemination associated with fire risk, fire protection, mitigation, safety, and emergency response.
Utilizes data science tools, resources, and software programs to further the mission and vision of ULRI in support of the fire service and greater public.
Supports fundamental knowledge needed to enhance ULRI’s thought leadership and support the strategy of ULRI.
Applies knowledge of and experience with spatial and temporal large-scale data, risk analysis methods, development of visualization outputs and other systems/resources to assist with various research projects and safety initiatives.
Supports the processing and visualization of mathematical and statistical models that analyze and predict current and future fire risk.
Works in collaboration with the software development team, informing and testing risk quantification methods and models at a national scale with resulting high performance.
Provides input into technical projects using information from experience and education to positively impact the fire service.
Stays informed of evolving technologies and emerging data science and sources in the field by reading journals and scientific publications and attending academic conferences.
Supports the planning, design, and implementation of procedures as needed to test and validate results.
Works with partner organizations, students, and teams.
Supports presentation of data science products and findings in various venues, as necessary.
Requirements
Bachelor’s degree in applied mathematics, statistics, data science, fire science, public health, fire protection engineering, mechanical engineering, geographic information systems, public policy, public administration, or a related field plus 8 or more years of directly related work experience, or
Master’s degree in applied mathematics, statistics, data science, fire science, public health, fire protection engineering, mechanical engineering, geographic information systems, public policy, public administration, or a related field plus 4 or more years of directly related work experience, or
Ph.D. plus 4 or more years of directly related work experience.
Demonstrated knowledge of and experience in developing, processing, and testing spatial and temporal data science methods for risk and resilience analysis, quantification, and associated geospatial products.
Demonstrated experience working with national-scale spatial data sets (e.g., parcel data, historical incident data, population demographic data, and remote sensing-derived data) at different spatial resolutions for integration in data science pipelines and product development.
Demonstrated skills and proficiencies in programming languages such as Python and R for data manipulation, statistical analysis, and model development.
Demonstrated skills and proficiencies with the use of GitHub for version control, managing, and collaborative data science project portfolios.
Demonstrated experience with GIS database structures and management, as well as analysis libraries such as Pandas, GIS visualization libraries (e.g., ArcGIS and QGIS) for production of geospatial analysis products.
Additional experience includes using ArcGIS Pro and ArcGIS Online tools (e.g., Survey123, Field Maps, Experience Builder, Dashboards) for data collection, geospatial visualizations, and rapid prototyping.
Familiarity with Amazon Web Services and cloud-based infrastructure for data storage, management, and basic computation is preferred.
Demonstrated ability to apply professional knowledge, experience, and other educational opportunities to support and improve fire safety and risk analysis.
Demonstrated ability to develop science-based academic and applied knowledge and skills.
Effective communication skills required.
Ability to collaborate with peers and work directly with Research Scientists and other team members to complete a project from start to finish.
Ability to contribute to writing research reports and papers.
Tech Stack
AWS
Cloud
Pandas
Python
Remote Sensing
Benefits
comprehensive medical, dental, vision, and life insurance plans
generous 401k matching structure of up to 5% of eligible pay
additional 4% into your retirement saving fund after your first year of continuous employment
flexible working arrangements
paid time off, including vacation, holiday, sick, and volunteer days