Senior Data Scientist

This role is for you if...

• You have a strong technical background and are wanting to use your skills on real-world, applied biodiversity conservation and restoration projects.
  
• You have ideas about how biodiversity data can be leveraged to make better decisions and you are excited to implement these.
  
• You are detail-oriented and diligent, with a keen understanding of the importance of well-curated data and a passion for creating pipelines to support this.
  
• You thrive in a remote work environment and are able to effectively manage your own workload without needing too much top-down direction.
  
• You enjoy working in a small, high-performance team and pitching in where you’re needed.
  

Requirements

• Must have: 5+ years of work experience and a degree in data science, computer science, statistics, mathematics, quantitative ecology or a related field plus 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). 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).
  

This role is for you if...

• You have a strong technical background and are wanting to use your skills on real-world, applied biodiversity conservation and restoration projects.
  
• You have ideas about how biodiversity data can be leveraged to make better decisions and you are excited to implement these.
  
• You are detail-oriented and diligent, with a keen understanding of the importance of well-curated data and a passion for creating pipelines to support this.
  
• You thrive in a remote work environment and are able to effectively manage your own workload without needing too much top-down direction.
  
• You enjoy working in a small, high-performance team and pitching in where you’re needed.
  

Requirements

• Must have: 5+ years of work experience and a degree in data science, computer science, statistics, mathematics, quantitative ecology or a related field plus 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). 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).