Senior Biometrician: Soil Carbon Quantification

PastureMap; San Antonio (TX); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Health insurance

Dental and vision insurance

Open PTO policy

401(k) savings plan

Company-paid life and AD&D insurance

Educational materials and expenses for

Job summary

Grassroots Carbon is seeking a biometrician, spatial statistician, or quantitative ecologist to design and evaluate methods estimating soil carbon stock change. You will combine field measurements, spatial data, and process models while accounting for uncertainty, using Bayesian hierarchical approaches and data assimilation to link observations over time.

The role emphasizes independent thinking, rigorous testing, and clear communication of methods and uncertainties to scientific peers, field

Qualifications

• A PhD, or an MS with an equivalent applied track record, in statistics, biostatistics, geostatistics, applied mathematics, or quantitative ecosystem science.
• Proven experience developing, documenting, and evaluating statistical methods through external regulatory, audit, or peer review.
• Strong applied experience with Bayesian hierarchical modeling, including model checking, uncertainty quantification, and sensitivity to assumptions. Familiarity with tools such as Stan, PyMC, or NumPyro.
• Practical experience with spatial sampling, repeated-measures inference, measurement-error analysis, and uncertainty propagation in heterogeneous environmental systems.
• Experience selecting and applying design-based, model-assisted, or model-based estimation, with an understanding of the assumptions and limitations of each.
• Strong R or Python skills, reproducible and versioned analytical workflows, and the ability to contribute to a Python-based production environment.
• The ability to communicate methods, evidence, and limitations clearly to scientific peers, field teams, executives, and external reviewers.

Responsibilities

• Sampling and Estimation: Design sampling and repeat-measurement programs for estimating carbon stocks and stock change at point, ranch, and portfolio scales.
• Measurement Quality and Comparability: Develop methods to distinguish ecological change from sampling, laboratory, and data-processing effects.
• Uncertainty Quantification: Develop hierarchical statistical models and propagate uncertainty from field sampling and laboratory measurements.
• Model Evaluation: Design independent tests of soil carbon and spatial prediction models across sites and time periods.
• Continuous Monitoring and Data Assimilation: Develop Bayesian hierarchical, state-space, and data-assimilation methods for combining measurements with models and remote sensing.
• Statistical Methods in Practice: Partner with engineers and field operators to implement reproducible workflows and documented procedures.
• Data Collection Priorities: Quantify benefits and costs of additional cores and monitoring to reduce uncertainty.

Skills

Bayesian modeling

Uncertainty quantification

Model checking

Sensitivity analysis

Spatial sampling

Repeated measures

Measurement error

R or Python

Reproducible workflows

Communicate methods

Education

PhD in statistics

MS with applied track in geostatistics

Applied mathematics

Tools

Stan

PyMC

NumPyro

xarray

GeoPandas

Job description

Grassroots Carbon is seeking a biometrician, spatial statistician, or quantitative ecologist to design and evaluate methods estimating soil carbon stock change. You will combine field measurements, spatial data, and process models while accounting for uncertainty, using Bayesian hierarchical approaches and data assimilation to link observations over time.

The role emphasizes independent thinking, rigorous testing, and clear communication of methods and uncertainties to scientific peers, field