Agricultural Data ScientistLearn

Legacy Farmer is always looking for growth-oriented, high performance people ready to deliver amazing results for our clients and team.

Location
Fully Remote

Uncapped PTO
Within Reason

The Agricultural Data Scientist will play a critical role in advancing Legacy Farmer’s mission by managing, cleaning, and interpreting both customer and internal data. This position is responsible for ensuring Legacy Farmer’s datasets are structured, accurate, and aligned with long-term objectives, including the development of AI models that support multi-level and cross-departmental functions.

The ideal candidate will have a deep agricultural background and advanced training in agricultural economics, statistics, or a related field. This person will understand the behaviors, decision-making patterns, and operational realities of agricultural producers, and will champion key initiatives to extract new foundational data that shapes company direction and trains AI systems.

This role will report directly to the Director of Engineering and the Director of Coaching
, ensuring tight integration between technical development and producer-facing coaching initiatives.

• Data Management & Preparation
  • Oversee the collection, cleaning, and organization of customer and internal datasets.
  • Ensure data integrity across multiple sources, including financial, operational, demographic, and spatial data.
  • Design pipelines that align data for long-term use in AI/ML model development.
• Data Analysis & Interpretation
  • Interpret complex agricultural data to provide actionable insights for the Director of Coaching, Director of Engineering, and the leadership team.
  • Monitor demographic, consumer behavior, and market trend data to identify opportunities and risks.
  • Translate producer behavior and operational metrics into predictive indicators for Legacy Farmer’s coaching and product teams.
• Survey Design & Data Collection
  • Develop and administer surveys of both internal members and external agricultural producers to gather high‑quality behavioral, financial, and demographic data.
  • Ensure survey instruments are statistically sound, unbiased, and aligned to produce representative insights.
  • Apply best practices to maximize survey response rates while protecting data quality.
  • Integrate survey results into the broader data strategy to support AI model training and leadership decision‑making.
• AI & Innovation Alignment
  • Collaborate with the Director of Engineering to ensure datasets meet technical requirements for AI/ML model training.
  • Collaborate with the Director of Coaching to ensure data reflects producer behaviors and operational realities.
  • Recommend and lead initiatives to extract new forms of foundational data critical for AI model training (e.g., farm‑level financial, spatial, and management practices data).
• Strategic Leadership Support
  • Present data‑driven findings and trends to the Director of Coaching, Director of Engineering, and leadership team to influence key business initiatives.
  • Support cross‑departmental projects by providing tailored data analysis and interpretation.
  • Ensure Legacy Farmer’s data strategy scales with organizational growth and evolving market demands.

• Master’s degree (MS) in Agricultural Economics, Statistics, or a closely related field.
• Strong academic background with a thesis or coursework directly aligned with agriculture, farm management, or producer economics.
• Agricultural background required — candidates must demonstrate experience, knowledge, or upbringing within the agricultural industry (no exceptions).
• Demonstrated high‑level proficiency in:
  • Data management (cleaning, structuring, pipelines).
  • Statistical analysis and econometric modeling.
  • Survey design, administration, and bias minimization.
  • Data visualization and communication of findings.
• Proven ability to interpret data and connect insights to real‑world agricultural decisions.
• Comfortable working in a fast‑changing, innovative environment.

• Experience working with farm‑level datasets, spatial data, or producer decision‑making data.
• Familiarity with agricultural market structures (banks, equipment dealers,…