Research Agronomist - Data & Modeling

The Research Agronomist - Data & Modeling will report to the Associate Director of Data Operations and Modeling. This is a research-first role with strong statistical grounding and advanced computational skills operating in ambiguity and independently driving high value work. This role operates at the intersection of agronomic research, spatial analytics, and product innovation, transforming large geospatial datasets into actionable insights that shape research direction, product strategy, and operational decisions. This position will strengthen analytical capability to directly drive Pivot Bio's product innovation pipeline and research strategy. This role will analyze data, shape decisions, design new analytical approaches, and help elevate how we use data across the organization., * Identify high-impact opportunities and independently initiate exploratory analyses.

• Prototype analytical methods to support Research Agronomy and Product Innovation
• Quantify uncertainty and guide risk-aware decisions.
• Engineer features from remote sensing data for modeling applications.
• Perform spatial analysis using Python, QGIS, and/or ESRI tools.
• Analyze plant growth dynamics across seasonal time periods.
• Perform EDA, field trial analysis, sensitivity analyses, and QC metric design.
• Develop and evaluate machine learning models when appropriate.
• Translate statistical outputs into clear, actionable recommendations.
• Use python and SQL to work within platforms such as Databricks and AWS
• Build reproducible research pipelines (data code outputs documentation)
• Contribute to ETL processes and partner closely with engineering.

Do you have experience in Statistical modeling?, Do you have a Master's degree?, * Advanced Python (pandas, numpy, geopandas, rasterio, scikit-learn).

• Strong SQL skills (Databricks or similar cloud warehouse experience preferred).
• Experience processing large geospatial raster datasets.
• Strong understanding of applied statistics and experimental design.
• Experience with feature engineering, modeling, and uncertainty quantification.
• Familiarity with cloud compute environments (AWS preferred).
• Experience building reproducible analytical workflows.
• Experience using GitHub

Complexity & Problem Solving

• Researcher mindset: curious, rigorous, and skeptical.
• Strong intuition for data quality and anomaly detection.
• Comfortable operating in ambiguity and prioritizing highest-impact work.
• Tenacious and self-directed, yet collaborative.
• Clear communicator who can translate complexity into action

Collaboration & Interaction

• Develop high-impact visualizations, presenting concise insights with clear next steps.
• Partner cross-functionally with research agronomists, product teams, and engineers.
• Coach peers and contribute to a strong Research Agronomy culture., * Master's degree (or equivalent experience) in Agronomy, Statistics, Data Science, Geospatial Analytics, or related field
• 2-4 years of experience in applied research, spatial analytics, or agronomic data science
• Experience working with satellite-derived datasets.
• Background in agricultural field trial analysis preferred.

Must be authorized to work in the United States

4.14.1 out of 5 stars Minneapolis, MN $91,600 - $114,500 a year, Pulled from the full job description

• 401(k) matching
• Vision insurance
• 401(k) 3% Match
• Dental insurance
• Stock options
• Employee assistance program
• Disability insurance, * Competitive package in a disruptive startup
• Stock options
• Health/Dental/Vision insurance with employer-paid premiums
• Life, Short-Term and Long-Term Disability policies
• Employee Assistance Program with free referrals and discounts
• 401(k) plan, 3% Match
• Commuter benefits
• Annual Training & Development support
• Flexible vacation policy with a generous holiday schedule
• Exciting opportunity to work with a talented and fun team

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