Perform robust statistical analyses of experimental and observational forest data
Evaluate and enhance current experimental design by performing power analyses and applying statistical models to multi-year trials
Rapidly prototype and deploy models connecting forest productivity to soil microbiomes and environmental factors, accounting for spatial and temporal dependencies
Enhance our carbon accounting system to incorporate incoming field-collected, genomic, and remotely sensed data
Build and validate pipelines for assessing the effectiveness of satellite and drone datasets for capturing on-the-ground measurements
Work closely with internal stakeholders on Growth, Applied Science, and other teams to ensure that insights meet their needs and accelerate their work
Travel up to 10-15% of the time for team offsite events, data collection, and stakeholder meetings as needed

Requirements

An MS or Ph.D. in a quantitative field (Statistics, Applied Mathematics, or equivalent experience)
Demonstrated expertise in hierarchical/mixed-effects models, longitudinal data analysis, repeated measures methods, and spatio-temporal modeling
High proficiency in SQL, R, and Python for data manipulation and modeling
Practical experience applying machine learning techniques to biological, environmental, or similarly complex systems
Familiarity with data integration, version control (Git), and reproducible research workflows (e.g. Markdown, Jupyter, Quarto)
Pragmatism balanced with rigor
A passion for biodiversity, ecosystem health, and climate action
Background in forest ecology, soil microbial ecology, or experimental design for field trials is a major plus
Experience with geospatial and remote sensing data analysis is a plus

Benefits

Comprehensive healthcare benefits
Employee equity programs
Flexible time off policy
Medical, dental, and vision benefits
Wellness reimbursement program

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

statistical analysesexperimental designpower analysesstatistical modelshierarchical modelsmixed-effects modelslongitudinal data analysisspatio-temporal modelingmachine learning techniquesdata manipulation

Soft Skills

pragmatismrigorcollaborationcommunication

Certifications

MS in quantitative fieldPh.D. in quantitative field