Scientific Analyst I (Extended Temporary) (Part-Time)

The Rangeland Hydrology and Erosion Model (RHEM) team of the School of Natural Resources and the Environment is looking for a motivated candidate to fill the role of Scientific Analyst I, preferably with a background in GIS, information systems, rangeland ecology, hydrology, soil science, or a related natural resource discipline, to help maintain and improve our established, actively used web-based tools. This is an excellent opportunity for a qualified candidate who seeks hands-on information systems development experience in the natural resource field. The successful candidate will support the maintenance of existing tools and the continued development of RHEM, while combining, manipulating, and visualizing datasets using Python and Esri's ArcGIS suite.

This is an Extended Temporary Employment (ETE) position expected to last a year from the start date with the possibility for extension dependent on available funding.

Visa sponsorship is not available for this position.

Outstanding U of A benefits include health, dental, vision, life insurance and disability programs; access to U of A recreation and cultural activities; and more!

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Data Preprocessing, Dataset
Harmonization & Data Documentation:

• Collect, clean, preprocess, and
  organize structured and unstructured rangeland ecology, hydrology, and soil
  science datasets into standardized, analysis-ready formats using Python and
  Esri's ArcGIS suite.
• Perform quality control measures
  and dataset testing to ensure data accuracy, completeness, and topology
  integrity.
• Document data sources, processing
  steps, and analytical methods to support transparency and repeatability for
  research collaborators and stakeholders.

Computational Module Support &
Process Automation:

• Support the RHEM research team in
  developing, evaluating, and maintaining scientific modules and database
  components for the web-based tool using Python and spatial information systems
  workflows under direct supervision.
• Identify opportunities to improve
  technical efficiency in routine data analysis and tool performance through
  script-based automation and standardized processing pipelines.

Data Visualization & Spatial
Analysis Output:

• Develop visual representations,
  summary graphics, and spatial data visualizations using Python and Esri's
  ArcGIS suite to demonstrate RHEM hydrology, soil erosion, and rangeland
  input/output data patterns and practical use cases for interdisciplinary research
  teams and stakeholders.

Tool Quality Testing &
Stakeholder Documentation:

• Perform quality assurance and
  functional testing on RHEM web tool modules and dataset inputs within defined
  guidelines.
• Support the preparation and
  enhancement of technical documentation, standard reports, and user
  training/instructional materials in varying formats to communicate data methods
  and system usage to stakeholders.

Knowledge, Skills, and Abilities
(KSAs):

• Proficient skill in Python for
  data processing, analysis, and visualization.
• Ability to compile, filter and
  summarize tabular data.
• Strong attention to detail for
  data QA, documentation, and testing.
• Ability to integrate heterogeneous
  tabular data from multiple sources.
• Solid written communication skills
  for user-facing documentation.
• Familiarity with the Esri/ArcGIS ecosystem.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

• Bachelor's degree or equivalent
  advanced learning attained through experience required.

• Bachelor's degree in rangeland ecology, hydrology, soil science, or a related natural resource discipline.
• Experience in building interactive data visualizations, version control with Git/GitHub.
• Experience working with Python, geospatial data and GIS, including preparing vector and raster files from provided source data.