Data Manager · Applied Data Scientist · Scientific Programmer

I build data systems and analysis workflows for complex, messy, real-world datasets. My primary background is in ecological and natural-resource programs, where I have worked on relational database design, GIS/spatial data processing, automated QA/QC, statistical modeling, technical reporting, and long-term data management.

Although most of my experience comes from scientific and environmental data, the core work is transferable across domains: structuring legacy datasets, improving data quality, building reproducible pipelines, integrating spatial and tabular data, and creating reliable outputs for analysis, reporting, and decision-making.

• Data management, QA/QC, and validation for complex real-world datasets
• Relational database design for scientific, spatial, operational, and reporting workflows
• Data integration across legacy databases, spreadsheets, GIS files, field-data systems, and structured text formats
• Reproducible processing, reporting, and analysis using SQL, Python, R, Markdown, and related tools
• Conversion of messy project data into clean, documented, analysis-ready outputs
• Spatial data processing, GIS workflows, and map/report-ready data products
• Automation tools for data cleaning, metadata extraction, reporting, ecological monitoring, soils, photo metadata, and camera-trap workflows
• Statistical modeling for longitudinal, spatial, ecological, and structured datasets

I design and maintain relational databases for ecological and spatial data, including schema design, primary/foreign key relationships, lookup tables, metadata tables, constraints, indexes, triggers, reporting views, and import / export workflows.

Common database tools:

• PostgreSQL / PostGIS
• SQLite / SpatiaLite
• DuckDB
• Microsoft Access / JET
• Microsoft SQL Server
• Spatial and tabular formats including GeoPackage, shapefiles, file geodatabases, CSV, JSON, XML, and Parquet

I use Python, R, and SQL to build data-processing workflows, automate QA/QC, summarize ecological indicators, generate reporting outputs, and prepare data for statistical analysis, GIS, and technical reports.

Common programming tools:

• Python
• R
• SQL
• VBA / Visual Basic
• Bash / shell scripting
• Markdown and LaTeX for technical documentation and reporting

I work with GIS data from field collection through reporting, including spatial data cleanup, geodatabase development, coordinate transformations, spatial joins and intersections, raster summaries, zonal statistics, map production, and GIS-ready outputs for technical and management audiences.

Common GIS / spatial tools:

• ArcGIS Pro & ArcPy/ModelBuilder
• QGIS
• GDAL
• PostGIS spatial SQL
• SpatiaLite
• R spatial packages including sf, stars, and spsurvey
• Python geopandas
• Pix4D, WebOpenDroneMap (WebODM)

My domain background is ecology and natural-resource monitoring, including:

• Ecological monitoring program data
• BLM AIM / DIMA workflows
• NRCS NRI / Landscape Monitoring Framework data
• SSURGO soils data
• Vegetation, soils, and ecological site data
• Rangeland, shrub-steppe, forest, prairie, oak savanna/woodland, and northern hardwood systems
• Bayesian mixed-effects modeling

A spatially enabled PostgreSQL/PostGIS database for storing, integrating, and querying ecological monitoring data from BLM AIM/DIMA and NRCS NRI/Landscape Monitoring Framework sources.

Project focus:

• Ecological monitoring database design
• PostgreSQL/PostGIS schema development
• Import/export workflows
• Materialized views
• Plot-level ecological indicator calculations
• R-based processing tools for species and user-defined indicators

A Python command-line tool for combining NRCS SSURGO soil survey downloads into spatially enabled SpatiaLite or PostGIS databases for GIS and ecological analysis workflows.

Project focus:

• Python command-line tooling
• SSURGO tabular and spatial data import
• SpatiaLite and PostGIS output databases
• Custom SQL views
• Dominant ecological-site polygons
• Custom ecological site groupings
• Geometry repair and snapping across adjacent soil survey areas

A database/reporting workflow for converting raw MS Access / ARS DIMA ecological field data into GIS-compatible, report-oriented outputs.

Project focus:

• Ecological monitoring QA/QC
• DIMA / AIM data processing
• SQLite database workflows
• Python GUI development
• Reporting outputs for field and program staff

Python command-line tools for extracting image hashes and EXIF metadata, storing photo metadata in relational databases, renaming files based on metadata, and reconnecting moved or renamed images using hash and filename matching.

Project focus:

• Image metadata extraction
• Relational storage of file paths, hashes, and EXIF tags
• SQLite and PostgreSQL support
• File renaming and path-repair workflows

Tools for managing camera-trap photo workflows, including sequence generation, random sampling, filtering detection outputs, and storing object ratings and bounding-box information.

Project focus:

• Camera-trap data organization
• Time/space-based image sequence generation
• Random sampling of detections
• Object rating and bounding-box storage
• Integration with photo metadata databases

I have more than 10 years of experience supporting ecological monitoring, geospatial analysis, relational database development, statistical modeling, and technical reporting for university, federal, and nonprofit natural-resource programs.

My academic background includes an M.S. in Animal and Rangeland Sciences from the University of Nevada, Reno, and a B.S. in Forestry from Iowa State University.

Selected research experience includes ecological monitoring, remote sensing, sapflow monitoring, camera-trap methods, grazing management, and Bayesian mixed-effects modeling for long-term vegetation and soil datasets.

Full publication list available on request.

For professional inquiries, contact me at:

wlieurance [at] gmail [dot] com

Full CV or résumé available on request.