Must have: 5+ years of work experience and a degree in data science, computer science, statistics, mathematics, quantitative ecology or a related field
Must have: Experience working with ecological/biodiversity data (e.g. camera trap images, passive acoustic monitoring recordings, vegetation surveys, animal surveys, species lists, soil carbon, biomass, remote sensing observation, climate etc.)
Must have: Strong Python for scientific data work - pandas or polars for data handling, plus the analysis stack (numpy, scipy, statsmodels, scikit-learn or equivalent)
Must have: Comfortable writing validation scripts that catch schema mismatches early and explain clearly what broke
Must have: Strong statistical reasoning, including an understanding of concepts such as confidence intervals, uncertainty estimation, GLMs, and discriminative machine learning models
Must have: Confident in SQL, joins, CTEs, window functions
Must have: Comfortable investigating data issues independently in pgAdmin, DBeaver, or similar
Strongly desired: Able to handle spatial data in PostGIS, QGIS, and GeoPandas - raster algebra, coordinate reference systems and reprojection, vector versus raster, and the common ways location data breaks
Strongly desired: Experience working with remote sensing data
Nice to have: Experience with ODK, KoboToolbox, Survey123, or a comparable field data collection platform (ODK Central admin experience is a plus)
GK
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