Job Description
- Leverage your statistical knowledge to clean, summarize, and visualize various field level data sets including internal datasets, government surveys, and other 3rd party agricultural survey data.
- Work with the Data Science and Data Engineering teams to assess the accuracy and quality of landscape scale data products (crop type, agricultural practice adoption, etc).
- Source reference data describing regional cropping and agricultural practices in the US, Europe, Brazil, and beyond.Â
- Oversee the collection of ground truth data collection for crop type, agricultural practices, and land use change.
- Apply best practices for sourcing, normalizing, and merging data from multiple sources (eg field surveys, self reported data, etc) for use in model training and assessment.
- Bachelor degree or equivalent experience in Earth Science, Remote Sensing, Computer Science, Statistics, or a related field.
- Experience using statistical techniques to evaluate tabular agricultural, forestry, or other natural resources data products.
- Strong SQL programming skills, preferably experience with BigQuery and Postgres.
- Experience creating data reports and visualizations using business intelligence tools like Looker or Tableau.Â
- Python programming skills, including scientific and data visualization libraries (pandas, NumPy, SciPy, PyViz, Jupyter, etc).
- Excellent English language technical writing and presentation skills.
- Ability to apply standard software development processes using Git and clearly document results.
- Familiarity with spatial statistics, remote sensing, and/or agronomy.
Date Posted
05/15/2024
Views
2
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