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Internship Agriculture Data Science Jobs (NOW HIRING)

Agricultural Data Scientist Legacy Farmer is always looking for growth‐oriented, high performance ... Strong academic background with a thesis or coursework directly aligned with agriculture, farm ...

Agricultural Data Scientist Legacy Farmer is always looking for growth‐oriented, high performance ... Strong academic background with a thesis or coursework directly aligned with agriculture, farm ...

Interns leave with a strong understanding of industry-standard data science practices and potential references for your career.

AgZen is a fast-growing precision agriculture company headquartered in Somerville, MA, built on MIT ... MS or PhD in Computer Science, Engineering, Statistics, Mathematics, Physics, or related field (or ...

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Internship Agriculture Data Science information

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How much do internship agriculture data science jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for internship agriculture data science in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What does an agriculture data science intern do?

An Agriculture Data Science Intern assists with collecting, analyzing, and interpreting agricultural data to help improve farming practices and productivity. They may work with large datasets related to crop yields, soil health, weather patterns, or supply chain management using statistical and machine learning tools. Their role often involves supporting research projects, creating data visualizations, and collaborating with agronomists or engineers. Through this experience, interns gain hands-on skills in both agriculture and data science, preparing them for future roles in agri-tech or research.

What are the key skills and qualifications needed to thrive as an agriculture data science intern, and why are they important?

To thrive as an Agriculture Data Science Intern, you need a solid grounding in statistics, data analysis, and agricultural science, typically supported by coursework or a degree in data science, agronomy, or a related field. Familiarity with programming languages like Python or R, data visualization tools, and experience with agricultural datasets or GIS systems are highly beneficial. Strong analytical thinking, problem-solving abilities, and effective communication skills set standout candidates apart. These skills and qualifications are crucial for interpreting complex agricultural data to drive informed decision-making and support innovation in the field.

What types of projects can I expect to work on during an agriculture data science internship?

As an Agriculture Data Science intern, you will typically work on projects involving the analysis of large datasets related to crop yields, soil health, weather patterns, or precision agriculture technologies. Common tasks include cleaning and processing agricultural data, building predictive models, and visualizing findings to support decision-making for farm management or research teams. You may also collaborate closely with agronomists, software engineers, and other data scientists, gaining exposure to both field and technical aspects of the industry. This hands-on experience helps develop practical skills and can open doors to advanced roles in agri-tech or research organizations.

What is the difference between Internship Agriculture Data Science vs Agriculture Data Analyst?

AspectInternship Agriculture Data ScienceAgriculture Data Analyst
CredentialsEnrolled in or recent graduate of relevant degree (e.g., data science, agriculture, statistics)Bachelor's or higher in data analysis, agriculture, or related fields
Work EnvironmentInternship programs, often in research or farm tech companiesFull-time roles in agricultural firms, research institutions, or tech companies
Employer & Industry UsageUsed by companies seeking entry-level data skills in agricultureUsed by organizations analyzing agricultural data for decision-making

Internship Agriculture Data Science positions are entry-level, focusing on learning and supporting data projects in agriculture. Agriculture Data Analysts are more experienced, responsible for analyzing data to inform agricultural strategies. Both roles require similar educational backgrounds but differ in experience and responsibilities.

More about Internship Agriculture Data Science jobs

What cities are hiring for Internship Agriculture Data Science jobs?

Cities with the most Internship Agriculture Data Science job openings:

What are the most commonly searched types of Agriculture Data Science jobs?

The most popular types of Agriculture Data Science jobs are:

What states have the most Internship Agriculture Data Science jobs?

States with the most job openings for Internship Agriculture Data Science jobs include:

Infographic showing various Internship Agriculture Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Agricultural Data Scientist

Legacy Farmer

Jackson, MS • Remote

Full-time

PTO

This job post has expired today. Applications are no longer accepted.


Job description

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

Location:

Fully Remote Office Hours: Flexible: 8 am – 6 pm Uncapped PTO: Within Reason Base Salary: + Commission Position Summary 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 behaviours, 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.

Key Responsibilities

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 behaviour 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 behavioural, 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 behaviours 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 organisational growth and evolving market demands.

Minimum Qualifications

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 modelling. Survey design, administration, and bias minimisation. 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.

Preferred Qualifications

Experience working with farm‐level datasets, spatial data, or producer decision‐making data. Familiarity with agricultural market structures (banks, equipment dealers, insurance, cooperatives). Understanding of AI/ML concepts and how training data influences model outcomes. Strong communication skills, able to translate complex findings into clear recommendations for both technical and non‐technical audiences. Additional Notes Candidates will be asked to demonstrate proficiency through a test as part of the interview process. This role requires both technical expertise in data and domain expertise in agriculture — only candidates with a verifiable agricultural background will be considered.

Summary:

The Agricultural Data Scientist ensures Legacy Farmer's data is managed, interpreted, and strategically leveraged to advance organisational initiatives and power AI‐driven tools. This role includes responsibility for designing unbiased surveys of agricultural producers to extract critical insights, maximise response rates, and integrate behavioural data into Legacy Farmer's AI and coaching models.