Senior 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 5–8 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 working directly with customers Experience building machine learning, statistical, or time series models informed by remotely-sensed data or large spatial datasets Good communication and collaboration skills with functional and cross-functional teams Ability to independently manage a project and deliver results

Train, improve, and deploy machine learning models for predicting soil carbon stock End-to-end deliveries for customers including model training, predictions, and report generation Interface directly with customers to understand needs and partner on solutions Collaborate with data scientists, engineers, and policy experts on data and methodology compliance Characterize accuracy and uncertainty of model predictions Execute full development cycle from exploratory data analysis to production model hardening Communicate research internally and externally