Position Summary
Legacy Farmer is seeking an Agricultural Data Scientist to own and develop producer-level economic and behavioral datasets that power product development, analytics, and AI systems.
This is a data-first role focused on structuring, validating, and analyzing farmer and rancher economic data. The role does not evaluate crop yields, livestock performance, or biological outcomes. Instead, it measures producer success, decision-making, and financial behavior across the agricultural economy.
The Agricultural Data Scientist reports directly to the VP of Product and works closely with engineering and product teams to ensure data is clean, interpretable, and production-ready.
What's in it for you?
- Location: Fully Remote
- Office Hours : Flexible 8:00am - 6:00 PM CST
- Uncapped PTO (within Reason)
What This Role Owns
- Producer-level economic and behavioral data
- Data quality, structure, and reproducibility
- Quantitative measurement of farmer and rancher success
- Data foundations for analytics, AI, and external data products
Key Responsibilities
Data Engineering & Management
- Collect, clean, normalize, and structure producer economic data, including:
- Financial statements and ratios
- Business structure and management indicators
- Demographic and enterprise characteristics
- Platform usage and engagement signals
- Build and maintain scalable data pipelines for analytics and modeling.
- Enforce data quality standards, validation rules, and documentation.
Quantitative Analysis & Modeling
- Apply statistical and econometric methods to:
- Identify patterns in producer decision-making
- Measure risk awareness, adoption behavior, and planning discipline
- Quantify relationships between financial behavior and outcomes
- Develop producer segmentation, scoring, and benchmarking frameworks.
- Monitor trends and anomalies across producer populations.
Primary Data & Survey Analytics
- Design, administer, and analyze statistically sound producer surveys.
- Convert survey responses into structured behavioral variables.
- Integrate primary survey data into core analytical datasets.
- Ensure sampling, weighting, and bias mitigation meet applied-economics standards.
Data Product & AI Readiness
- Structure datasets to support:
- Predictive analytics
- AI/ML training
- Partner-facing intelligence products
- Work with engineering to ensure datasets are production-ready.
- Identify and close gaps in producer-economic data coverage.
Product & Leadership Reporting
- Deliver clear, data-driven insights to the VP of Product and product teams.
- Build repeatable reports, dashboards, and documentation.
- Ensure analytical conclusions are traceable to well-defined data sources.
Minimum Qualifications
- Master's degree (MS) in Agricultural Economics, Applied Economics, Economics,
Statistics, or a closely related field.
- Strong quantitative background in:
- Econometrics
- Applied statistics
- Data analysis
- Demonstrated experience working with:
- Large, messy datasets
- Data cleaning and transformation
- Reproducible analytical workflows
- Agricultural background required (farm/ranch experience, ag industry exposure, or applied ag-econ research).
- Ability to translate data into practical producer-economic insights.
Preferred Qualifications
- Experience with:
- Producer-level financial data
- Survey microdata and behavioral datasets
- Benchmarking or underwriting-adjacent analytics
- Familiarity with:
- Agricultural lending, insurance, or agribusiness markets
- Working knowledge of:
- SQL, Python, or R
- Data visualization tools
- AI/ML data requirements
- Strong technical documentation skills.
Explicit Scope Clarification
In Scope
- Farmer and rancher financial behavior
- Economic decision-making and awareness
- Risk management and planning outcomes
Out of Scope
- Crop yields, agronomy, or soil data
- Livestock health, genetics, or production metrics
- Biological performance indicators
Role Summary
The Agricultural Data Scientist owns the data layer that measures farmer and rancher
success across the agricultural economy. Reporting to the VP of Product, this role ensures producer-economic data is clean, structured, and analytically useful for product decisions, AI systems, and external intelligence offerings-without engaging in crop or animal science.
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