Data Management Analyst II
About The Position
The Data Management Analyst II will be responsible for developing and implementing data management procedures for complex environmental and geospatial datasets supporting Everglades restoration monitoring. This role involves acquiring, organizing, cleaning, standardizing, and integrating various types of data including aerial imagery, satellite imagery, LiDAR, RECOVER MAP measurements, hydrologic layers, fire-history datasets, vegetation data, and field measurements. The analyst will maintain appropriate file structures, naming conventions, metadata, version control, and documentation to ensure data quality, traceability, and reproducibility. Additionally, the position requires conducting geospatial and remote sensing analyses to support mapping and assessment of ecological and hydrologic indicators, applying GIS, image-processing, statistical, and machine-learning methods to develop spatially explicit environmental data products. The role also includes developing and implementing quality assurance and quality control procedures, evaluating datasets for data-quality concerns, supporting accuracy assessment of analytical products, and documenting uncertainty and limitations. Collaboration with faculty, specialists, and students is essential for coordinating data needs and analytical activities. The analyst will also participate in project meetings, provide technical input, and contribute to developing research proposals for funding opportunities.
Requirements
- Master’s degree in an appropriate area; or a bachelor’s degree in an appropriate area and two years of relevant experience.
Nice To Haves
- Master's Degree.
- Excellent communication, organization, and leadership skills.
Responsibilities
- Develop and implement data-management procedures for complex environmental and geospatial datasets supporting Everglades restoration monitoring.
- Acquire, organize, clean, standardize, and integrate aerial imagery, satellite imagery, LiDAR, RECOVER MAP measurements, hydrologic layers, fire-history datasets, vegetation data, field measurements, and other project datasets.
- Maintain appropriate file structures, naming conventions, metadata, version control, and documentation to ensure data quality, traceability, and reproducibility.
- Conduct geospatial and remote sensing analyses to support mapping and assessment of ridge, slough, tree island, and transitional vegetation classes; vegetation density; aboveground biomass; fuel-density indicators; and other ecological and hydrologic indicators.
- Apply appropriate GIS, image-processing, statistical, and machine-learning methods to develop spatially explicit environmental data products.
- Assist with development of spatially explicit Manning roughness coefficient surfaces and related crosswalk tables for hydrodynamic modeling.
- Develop and implement quality assurance and quality control procedures for project datasets and analytical outputs.
- Evaluate datasets for coordinate-system consistency, missing or anomalous observations, acquisition-date issues, spatial artifacts, and other data-quality concerns.
- Support accuracy assessment of classification and modeling products using independent validation data and appropriate statistical performance measures.
- Document uncertainty, limitations, assumptions, and appropriate use of analytical products.
- Collaborate with faculty, remote sensing specialists, graduate students, and other project personnel to coordinate data needs, analytical activities, project milestones, and technical deliverables.
- Participate in project meetings and provide technical input regarding data management, geospatial analysis, and interpretation of results.
- Participate in developing and writing competitive research proposals for state and federal funding opportunities.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
