Data Scientist

Master's degree or Ph.D. in statistics, math, computer science, remote sensing, AI/ML, ecosystem science, soil science, geography, or a related STEM field 3–6 years of industry or research experience in data science, applied ML, geospatial analysis, or related fields Strong proficiency in Python for data science (e.g. pandas, scikit-learn, xarray, numpy) Experience building machine learning, statistical, or time series models informed by remotely-sensed data or large spatial datasets Good communication and collaboration skills Ability to independently manage a project and deliver results

Build, improve, and deploy machine learning models for predicting soil carbon stock Manage end-to-end customer deliveries: train models, run predictions, ensure quality Collaborate with teams to ensure data and methods comply with standards Characterize accuracy and uncertainty of model predictions Execute full development cycle from EDA to production hardening Communicate research internally and externally through documentation, presentations, and publications