Biometrician: Soil Carbon Quantification & Modeling

Grassroots Carbon; San Antonio (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health Insurance

Dental & Vision

401(k)

Paid Time Off

Educational support

Job summary

Grassroots Carbon in San Antonio, TX, is seeking a biometrician, spatial statistician, or quantitative ecologist to design and implement methods for estimating soil carbon stock change using imperfect data.

You will combine field measurements, spatial info, and process models, with emphasis on uncertainty, Bayesian approaches, and continuous monitoring.

This role supports regenerative grazing outcomes and collaboration across science, engineering, and field teams.

Qualifications

• PhD or MS with applied track record in statistics or quantitative ecosystem science.
• Proven experience developing, documenting, and evaluating statistical methods.
• Strong Bayesian modeling, uncertainty quantification, and model checking.
• Practical experience with design-based, model-assisted, or model-based estimation.
• Strong R or Python skills with reproducible workflows.

Responsibilities

• Design sampling and repeat-measurement programs for estimating carbon stocks and changes.
• Develop estimators with area weighting, spatial dependence, and missing observations.
• Distinguish ecological change from measurement and lab effects with QC design.
• Create hierarchical models and propagate uncertainty through calculations.
• Evaluate biases, predictive accuracy, and uncertainty coverage across sites.
• Develop Bayesian, state-space, and data-assimilation methods for monitoring.
• Document methods, uncertainty, and limitations for external review.

Skills

Bayesian modeling

R or Python

Uncertainty quantification

Spatial sampling

Model evaluation

Data assimilation

State-space models

Education

PhD in statistics or related field

MS with applied track record

Tools

Stan

PyMC

NumPyro

xarray

GeoPandas

Job description

Grassroots Carbon in San Antonio, TX, is seeking a biometrician, spatial statistician, or quantitative ecologist to design and implement methods for estimating soil carbon stock change using imperfect data.

You will combine field measurements, spatial info, and process models, with emphasis on uncertainty, Bayesian approaches, and continuous monitoring.

This role supports regenerative grazing outcomes and collaboration across science, engineering, and field teams.