Data Scientist ArcGIS

Role Overview

We are seeking an Agronomic Data Analyst / Science Engineer to sit at the intersection of data science, applied analytics, and agricultural research. This role will support the acceleration of business actionable insights derived from R&D experimental results, manufacturing data, and field trials. You will work collaboratively across R&D, Information Technology, and commercial teams to transform complex datasets into insights that improve product performance, operational efficiency, and market outcomes.

• Data Analysis & Insight Generation
• Cross-Functional Collaboration

Analyze complex datasets from product development, field testing, manufacturing systems, and commercial channels to enable data-driven decision-making.

Collaborate with R&D analysts and agronomists to aggregate results from Answer Plots, On-Farm trials, and controlled experiments into statistically sound and geospatially relevant business insights.

Transform R&D and operational data into actionable insights to support manufacturing optimization, product performance, and sales/marketing strategy.

Interpret and communicate results to stakeholders to ensure technologies proper movement through approved processes.

Build, analyze, and optimize datasets using Python/R and SQL.

Participate in the creation and maintenance of long-term data solutions for data mining, storage, and high-throughput analytics.

Collaborate on implementing automated data pipelines and reproducible data workflows with version control and documentation.

Assist in the creation of business-focused semantic data layers that accelerate the translation of experimental results into insights.

• Mid-level experience in data science, analytics, or data engineering.
• Ability to translate technical findings into insights relevant to agricultural manufacturing and commercial teams.

• Education: Bachelor’s degree in a quantitative or technical field (e.g., Data Science, Computer Science, Engineering, Statistics, Mathematics, Agricultural Engineering, or related field).
• Technical Proficiency: Proficiency in Python and/or R for data analysis and modeling.
• Strong SQL and relational skills for querying and managing structured datasets.
• Experience using business analytics tools (e.g., Power BI) and applying quantitative methods.

• Geospatial
  
  Skills:
  
  Experience with geospatial analytics, spatial statistics, and tools such as ArcGIS (Pro, Enterprise, Online) or other GIS applications for field/spatial data.
• Domain Knowledge: Background in agronomy, plant biology, or ecology, or familiarity with agricultural datasets and sensor/field-generated data.
• Platform
  
  Experience:
  
  Experience working with enterprise data platforms such as Databricks and Snowflake.
• Advanced Analytics: Experience with image-based AI interpretation, remote sensing, or machine learning algorithms to extract plant traits.
• Growth & Development This position offers a clear path for professional growth within a technology-driven agricultural organization, providing hands-on exposure to R&D initiatives that directly impact agricultural productivity and sustainability. You will have the opportunity to expand your skills across ag-tech, data science, AI, and manufacturing analytics.