Geospatial Analyst

Duties and Accountabilities:

The ITS geospatial team is seeking a Geospatial Data Analyst to enhance our geospatial solution development and implementation efforts. This role offers the chance to drive data-centric innovation and deliver analytical prowess to both our internal and external stakeholders. The ideal candidate will thrive in cross-functional and Agile team environments and possess comprehensive knowledge in the following areas:

• Collect and document requirements about applications and data from key business stakeholders.

• Collect, document, analyze, and interpret geospatial datasets to host and curate for our applications and end users.

• Support data management efforts through data cleaning and extract, transform, and load (ETL) processes (e.g. consolidate separate datasets in different formats into a PostgreSQL table keeping shared attributes).

• Analyze and process raster and vector data to create analytical outputs (e.g. land cover classification)

• Use desktop and web software to create map visualizations.

• Write reusable code in Python to automate workflows.

• Automate imagery processing using cloud platforms like Google Earth Engine or Microsoft Planetary Computer

Selection Criteria:

• Master's degree in a quantitative discipline such as Geospatial data science, earth science, quantitative social sciences, geographic information system, physics, or a related field.

• Demonstrated experience using quantitative and qualitative techniques to solve complex problems using analytic tools and techniques such as GIS, quantitative methods and data visualization, modeling, systems analysis, comparative analysis, and database development.

• Demonstrated knowledge and experience in data mining, cleansing, and exploring spatial, temporal, and non-spatial data in both structured and unstructured formats.

• Demonstrated knowledge of programming languages (e.g., Python, Java, JavaScript, SQL, Pig or R), modeling software, spatial analysis tools and concepts, data mining methods, database structures and analytic information extraction and visualization.

• Experience with Geospatial Tools (e.g., ArcGIS, QGIS) and/or geospatial approaches (spatial analysis, remote sensing, network analysis, geographic visualization, etc.)

• Familiarity with open-source GIS such as GDAL (including OGR), QGIS, and familiarity with 3D GIS data and extracting and processing Open Street Map data.