Senior Research Statistician

Pivot Path Solutions•Washington, DC

1d•Onsite

About The Position

Pivot Path Solutions, LLC is seeking a Senior Research Statistician to support advanced statistical and data science research for the U.S. Department of Agriculture’s National Agricultural Statistics Service (USDA NASS). This position will support the modernization of official agricultural statistics through innovative statistical methods, artificial intelligence, machine learning, and the integration of survey and non-survey data. The Senior Research Statistician will lead day-to-day research activities and develop production-ready statistical methodologies, software, documentation, and research products for operational use by NASS.

Requirements

Ph.D. in Statistics or a closely related quantitative field.
At least 10 years of professional research experience conducting recognized statistical or data science research with direct application to agriculture.
Demonstrated expertise in: Bayesian statistics, Small-area estimation, Survey methodology, Machine learning and artificial intelligence, Geospatial data integration, Record linkage and entity resolution, Large language models, Adaptive survey design, Reproducible research methods
Extensive experience working with agricultural survey and non-survey data.
Strong record of publications involving the analysis of agricultural data.
Ability to develop research methodologies and software suitable for operational implementation.
Strong technical writing, communication, and collaboration skills.

Responsibilities

Develop statistical methodologies supporting NASS agricultural survey and census programs.
Develop Bayesian and small-area estimation models.
Analyze and model agricultural survey and non-survey data.
Integrate survey, administrative, remotely sensed, economic, weather, soil, and geospatial data.
Develop machine learning methods for anomaly detection, classification, and adaptive survey design.
Apply AI-assisted geospatial harmonization techniques.
Use large language models to improve metadata extraction, documentation, and research workflow efficiency.
Perform record linkage and entity-resolution research.
Develop capture-recapture and calibration algorithms to adjust record-level weights and assess uncertainty against established population benchmarks.
Create reproducible, version-controlled research pipelines.
Evaluate state-level estimates for conservation data products.
Apply statistical disclosure-limitation methods to protect the privacy and confidentiality of farmers’ data before publication.
Participate in monthly meetings with the Government and quarterly technical reviews.
Prepare quarterly progress reports, annual research reports, and publication-quality technical papers.
Develop production-ready software, technical documentation, and knowledge-transfer materials.