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Internship Agriculture Data Analytics Jobs (NOW HIRING)

Trinity Industries

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position will focus on building, deploying, and scaling agentic AI applications and automated workflows ...

TrinityRail

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position will focus on building, deploying, and scaling agentic AI applications and automated workflows ...

247Hire

Data Scientist

Austin, TX · On-site

$90 - $130/hr

Develop and deliver production-ready machine learning approaches to yield insights and recommendations from precision agriculture data. * Define, quantify, and analyze Key Performance Indicators that ...

New

Microsoft

Senior Manager - Data Analytics

Redmond, WA · On-site

... prior roles, internships, or coursework. * Experience with Python, R, or another scripting ... Data Analytics IC4 - The typical base pay range for this role across the U.S. is USD $106,400 ...

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

As of Aug 8, 2026, the average hourly pay for internship agriculture data analytics 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 types of projects can I expect to work on during an agriculture data analytics internship?

As an Agriculture Data Analytics intern, you'll likely work on projects involving data collection, analysis, and visualization to support crop management, yield prediction, or resource optimization. You may collaborate with agronomists and data scientists to clean and interpret large datasets from sources like precision agriculture tools or remote sensors. Interns often contribute to building dashboards, generating reports, and creating actionable insights that help improve farming practices. This role offers hands-on experience with both agricultural concepts and analytical tools, providing a valuable foundation for a career in agri-tech or data science.

What is an internship in agriculture data analytics?

An Internship in Agriculture Data Analytics is a temporary position designed for students or recent graduates to gain practical experience in analyzing agricultural data. Interns typically work with large datasets related to crop yields, soil health, weather patterns, and farm management practices, using statistical tools and software. The goal is to generate actionable insights that help improve agricultural productivity, sustainability, and decision-making. Interns may also assist with data collection, cleaning, and visualization, working under the supervision of experienced data analysts or agricultural scientists.

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

AspectInternship Agriculture Data AnalyticsAgriculture Data Analyst
Required CredentialsEnrolled in or recent graduate of relevant degree programsBachelor's or higher in data science, agriculture, or related fields
Work EnvironmentInternship setting, often in agricultural companies or research centersFull-time professional role in agriculture or data firms
Employer & Industry UsageEducational, training-focused, often temporaryOperational, decision-making role within agriculture industry
Search & Comparison IntentLearning about entry-level opportunities and trainingUnderstanding professional career paths and job requirements

Internship Agriculture Data Analytics is a temporary, training-focused position for students or recent graduates, emphasizing learning and skill development. In contrast, an Agriculture Data Analyst is a full-time professional role requiring more experience and responsibility, focusing on analyzing agricultural data to support business decisions.

What are the key skills and qualifications needed to thrive as an internship in agriculture data analytics?

To excel in an Internship Agriculture Data Analytics role, you need a solid understanding of data analysis, statistics, and foundational knowledge of agriculture, often backed by coursework in data science or agronomy. Familiarity with tools like Python, R, Excel, and agricultural data management platforms is typically required. Strong analytical thinking, attention to detail, and effective communication will help you interpret findings and collaborate with multidisciplinary teams. These skills are crucial for turning raw agricultural data into actionable insights that can improve farming efficiency and sustainability.
More about Internship Agriculture Data Analytics jobs
What cities are hiring for Internship Agriculture Data Analytics jobs? Cities with the most Internship Agriculture Data Analytics job openings:
What are the most commonly searched types of Agriculture Data Analytics jobs? The most popular types of Agriculture Data Analytics jobs are:
What states have the most Internship Agriculture Data Analytics jobs? States with the most job openings for Internship Agriculture Data Analytics jobs include:
What job categories do people searching Internship Agriculture Data Analytics jobs look for? The top searched job categories for Internship Agriculture Data Analytics jobs are:
Internship Agriculture Data Analytics jobs near you
Infographic showing various Internship Agriculture Data Analytics job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Data Analytics Intern

Trinity Industries

Dallas, TX • On-site

Internship

Re-posted 8 days ago

Trinity Industries rating

6.5

Company rating: 6.5 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

404th of 487 rated machine equipment manufacturers

Job description

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX. This position will focus on building, deploying, and scaling agentic AI applications and automated workflows across the enterprise. You will contribute to producing AI-first solutions using large language models, agent frameworks, and AI-assisted coding to deliver deployable apps, agents, automated workflows, and AI orchestration.
This role will provide valuable experience working with state-of-the-art enterprise platforms (Databricks and Palantir Foundry) and AI tools (pro licenses for Codex and Claude Code). The role offers hands-on mentorship from senior analytics professionals, exposure to production data and governance practices, and high visibility to business owners giving you real ownership of high-impact projects.
What You'll Do:
  • Design, prototype, and deliver agentic systems that plan and execute multi-step business tasks.
  • Build automated workflows and connectors that integrate internal systems and APIs.
  • Implement LLM-based agents (prompting, tool-calling, memory, monitoring) and harden prototypes for handoff.
  • Produce code and deployable artifacts using AI-assisted generation.
  • Collaborate with data analysts, data scientists, and data engineers as well as stakeholders to gain in-dept knowledge of business problems and likely solutions.
  • Demo results and deliver concise handoff docs, runbooks, and impact metrics.

What You'll Have:
  • Master's or PhD candidate or recent graduate in Data Science, Machine Learning, Computer Science, Applied Math, Statistics, Operations Research, or similar quantitative field.
  • Demonstrable experience building AI prototypes or agentic projects (coursework, research, personal projects, or employment).
  • Generate, test, and iterate code (examples: Python, JavaScript, YAML) using an IDE (VS Code, JetBrains, etc.) with AI-assisted coding (GitHub Copilot, OpenAI Codex,
  • Claude Code, Cursor, or similar). Manual coding fluency is helpful but not mandatory.
  • Familiarity with SQL and cloud data platforms (Databricks, Azure, AWS, or equivalent).
  • Strong problem solving and communication skills; ability to present technical work to nontechnical stakeholders.

Preferred / Nice-to-Have
  • Practical experience with model deployment and monitoring basics (packaging/deploying prototypes, logging/observability, basic cost and drift checks).
  • Experience building or working with data/workflow pipelines or orchestration tools or familiarity with the concepts of scheduling and task orchestration.
  • Experience working with unstructured text and retrieval approaches (RAG or index + LLM patterns) for document/question answering.
  • Comfortable integrating services via REST APIs and using secure authentication patterns.

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