Ledelsea
Data Scientist With ArcGIS
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a contract-to-hire Data Scientist with ArcGIS, requiring local candidates from the Minneapolis/St. Paul area. Key skills include Python, R, SQL, and geospatial analytics. A bachelor's degree in a quantitative field and mid-level experience in data science are required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 4, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Greater Minneapolis-St. Paul Area
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🧠 - Skills detailed
#Data Mining #Python #Data Quality #AI (Artificial Intelligence) #Data Analysis #Databricks #Snowflake #Data Pipeline #Data Management #Data Engineering #BI (Business Intelligence) #Data Layers #Statistics #Datasets #SQL (Structured Query Language) #Strategy #ML (Machine Learning) #Mathematics #Storage #Version Control #"ETL (Extract #Transform #Load)" #Microsoft Power BI #R #Spatial Data #Documentation #Computer Science #Data Science
Role description
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• This is a contract to hire role, only currently accepting candidates currently local to the Minneapolis/St. Paul area
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• Will not be able to consider candidates needing to relocate or unavailable for onsite/in person interviews
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• Please do not apply if you are not currently living in Minnesota, Thank you!
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• 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.
Key Responsibilities
• Data Analysis & Insight Generation
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 AnswerPlots, 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.
• Data Management & Pipeline Development
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.
• Cross-Functional Collaboration
Work with FP&A personnel to identify areas where advanced analytics can increase efficiencies and uncover new insights.
Collaborate with field and controlled environment researchers to optimize data collection protocols and ensure data quality for product evaluation.
Support innovation initiatives focused on agricultural solutions, including biological product characterization both in-field and in controlled environments.
Required Qualifications
• 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.
Experience:
Mid-level experience in data science, analytics, or data engineering.
Ability to translate technical findings into insights relevant to agricultural manufacturing and commercial teams.
Preferred & Nice-to-Have Qualifications:
• 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.
•
•
•
•
•
•
• This is a contract to hire role, only currently accepting candidates currently local to the Minneapolis/St. Paul area
•
•
•
•
•
•
•
•
•
•
•
•
•
• Will not be able to consider candidates needing to relocate or unavailable for onsite/in person interviews
•
•
•
•
•
•
•
•
•
•
•
•
•
• Please do not apply if you are not currently living in Minnesota, Thank you!
•
•
•
•
•
•
• 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.
Key Responsibilities
• Data Analysis & Insight Generation
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 AnswerPlots, 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.
• Data Management & Pipeline Development
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.
• Cross-Functional Collaboration
Work with FP&A personnel to identify areas where advanced analytics can increase efficiencies and uncover new insights.
Collaborate with field and controlled environment researchers to optimize data collection protocols and ensure data quality for product evaluation.
Support innovation initiatives focused on agricultural solutions, including biological product characterization both in-field and in controlled environments.
Required Qualifications
• 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.
Experience:
Mid-level experience in data science, analytics, or data engineering.
Ability to translate technical findings into insights relevant to agricultural manufacturing and commercial teams.
Preferred & Nice-to-Have Qualifications:
• 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.
