Data Scientist

• Build, improve, and deploy machine learning models for predicting soil carbon stock with remotely-sensed covariate data and limited training data
• End-to-end deliveries for customers: train models, run predictions, and ensure quality results are delivered in customer reports
• Work with other data scientists, engineers, and policy experts to ensure data and methods comply with various standards and methodology requirements
• Characterize the accuracy and uncertainty of model predictions and demonstrate performance metrics dependence on carbon project parameters

This role helps quantify changes in soil organic carbon stocks in agricultural soils, advancing digital soil mapping to bring it into voluntary carbon markets, which supports climate-smart agriculture and helps decarbonize the food supply chain.

• Master's degree or Ph.D. in statistics, math, computer science, remote sensing, AI/ML, ecosystem science, soil science, geography, or 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

• Competitive compensation packages with starting salary range of USD $120,000-$145,000 (commensurate with experience and location)
• Equity in the company
• Generous PTO, health, vision, dental, 401k, and HSA benefits
• Fully stocked kitchen
• Professional development opportunities
• Mission-driven collaborative environment
• Fully-flexible remote and hybrid work options

Perennial is building the world's leading verification platform for soil-based carbon removal with a vision to unlock soil as one of the world's largest carbon sinks. They build trusted standards, tools, and technologies to help verify climate-smart agriculture using advanced remote measurement technology for soil carbon sequestration and emissions.