Geospatial Data Scientist
Posted on 3/3/2023
The Climate Corporation
Digital agriculture company
Company Overview
Climate's mission is to help the world’s farmers sustainably increase productivity with digital tools. The next breakthrough in agriculture will utilize data and analytics to optimize the many decisions farmers must make throughout the growing season and in planning their operations.
Seattle, WA, USA • Chicago, IL, USA • St. Louis, MO, USA
Experience Level
Desired Skills
Data Analysis
Data Science
Data Structures & Algorithms
Microsoft Azure
AI & Machine Learning
Data & Analytics
DevOps & Infrastructure
  • MS in Statistics, Data Science, Math, Physics, Computer Science, Engineering, Soil Science, Geography, or other highly quantitative discipline + 2-year experience conducting geospatial data analysis and modeling, or PhD in one of the aforementioned disciplines
  • Demonstrated experience with remote sensing, agricultural, and/or large geospatial data
  • Demonstrated ability to apply statistical methods and/or data science to real world problems
  • Demonstrated knowledge of and experience with processing and analyzing large geospatial datasets, assessing the effectiveness and accuracy of new data sources and data gathering techniques
  • Skilled in the use of Python and SQL for research, data analysis, and/or modeling
  • Clean, munge, and explore diverse environmental, EO remote sensing and/or geospatial datasets
  • Develop environmental and geospatial layers, and test these layers in predictive models
  • Analyze and judge the quality of data, and work with the data quality team to resolve issues
  • Design, prototype, and implement models to explore spatio-temporal dynamics and variability in agricultural fields using diverse techniques that include, but are not limited to process modeling, statistical modeling, machine learning, data mining, and optimization
  • Collaborate with other data scientists and engineers in developing models to characterize, diagnose and/or predict patterns of crop performance
  • Write robust, well-documented, and well-tested research code and code libraries that adhere to community standards and best practices
Desired Qualifications
  • Outstanding knowledge of Earth Observation satellite data from multiple sources and spectral regions (e.g. optical, RADAR) theory, sensors as well as its main applications to agriculture
  • Experience with processing remote sensing optical and SAR data using python, open source or off-the-shelf software tools
  • Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning and predictive analytics
  • Experience using spatial and time-series statistical methods to solve agricultural research problems
  • Experience in designing, developing, and testing geospatial pipelines applied to machine learning model generation and deployment
  • Experience using version control systems, e.g. git
  • Experience working with cloud technologies or distributed computing platforms such as AWS, Azure, Google Cloud etc