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Internship Agriculture Data Science Jobs in Raleigh, NC

NCSU

Lecturer of Data Science

Raleigh, NC

$4.0K/wk

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

NCSU

Lecturer of Data Science

Raleigh, NC

$4.0K/wk

The Data Science and AI Academy's goal is to network and catalyze data science across all three ... Data Internships Preparation for Social Impact * Exploring Machine Learning Appointments will be ...

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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 Aug 30, 2026, the average hourly pay for internship agriculture data science in Raleigh, NC is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 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.

What are the most commonly searched types of Agriculture Data Science jobs in Raleigh, NC?

The most popular types of Agriculture Data Science jobs in Raleigh, NC are:

What are popular job titles related to Internship Agriculture Data Science jobs in Raleigh, NC?

For Internship Agriculture Data Science jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Internship Agriculture Data Science jobs in Raleigh, NC look for?

The top searched job categories for Internship Agriculture Data Science jobs in Raleigh, NC are:

Internship Agriculture Data Science jobs near you
Infographic showing various Internship Agriculture Data Science job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $45,502 per year, or $21.9 per hour.

Applied Genetics Scientist - Pipeline Data Science

Durham, NC • Hybrid

Syngenta
See more jobs at Syngentaexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

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

Job description

Company Description

About Syngenta

Syngenta is a leading developer and producer of seeds. We bring farmers stronger, more vigorous, resistant plants, including innovative hybrid varieties and biotech crops that can thrive even in challenging growing conditions. Each of our 28,000 employees in more than 90 countries work together to solve one of humanity's most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. 

Job Description

Applied Scientist - Pipeline Data Science

  • Type: Permanent 
  • Department: Seeds Development / Vegetables
  • Location: Enkhuizen - NL, RTP - US

Into action

Do you thrive at the intersection of data engineering, predictive analytics, and innovation? As our Applied Scientist - Pipeline Data Science, you will play a crucial role in designing scalable data solutions that drive actionable insights. By consolidating complex datasets into robust, efficient pipelines, you'll empower teams to make better decisions and uncover new possibilities in plant breeding. This is your opportunity to work on impactful projects in a collaborative and cutting-edge environment where data drives transformation. 

The challenge

As an Applied Scientist, you'll focus on building the infrastructure that makes data accessible, reliable, and actionable for diverse stakeholders. Your key responsibilities will include: 

  • Building Scalable Data Pipelines: Design, implement, and optimize data pipelines that integrate and consolidate data from multiple sources, ensuring seamless data flow and availability. 
  • Ensuring Data Quality and Reliability: Contribute to data mining, curation, analytics and visualization of data sets to gain deep understanding of the crop(s) and enable successful application of technology
  • Driving Data Modeling and Mining: Create and implement processes for advanced data modeling and mining to support innovative analytical approaches. 
  • Collaborating Across Teams: Work closely with IT, applied data science teams, and business stakeholders to align data solutions with organizational goals, addressing unique data needs efficiently. 
  • Identify opportunities to incorporate advanced analytics, including machine learning frameworks and cloud platforms to continuously improve predictive pipelines.
  • Influence adoption of genomic prediction methods, contribute towards their integration in the breeding process and the transformation of respective breeding schemes

This role combines creativity and problem-solving with a focus on real-world applications. You'll not only shape the way data is managed but also contribute to meaningful outcomes in plant breeding and sustainable agriculture. Every dataset you refine and every system you enhance will drive smarter decisions and impactful innovations. 

Qualifications

Your profile

PLEASE NOTE: Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This comprises, but is not limited to, OPT, CPT, and H-1B visa holders.

We seek a detail-oriented Applied Scientist with a Master's in Computer Science, Statistics, Applied Mathematics, Quantitative Genetics, or related fields. You combine strong technical skills, analytical insight, and a collaborative mindset.

  • Programming: Skilled in Python, R, SQL; experienced with relational and NoSQL databases.
  • Cloud: Familiar with AWS services and infrastructure.
  • Analytics: Able to uncover patterns in large datasets and translate findings into actionable recommendations.
  • Collaboration: Effective team player, able to communicate technical concepts to diverse stakeholders.
  • Bonus: Experience with Docker/Kubernetes, machine learning frameworks (Keras, PyTorch, scikit-learn), and interest in plant breeding or agricultural innovation.
Additional Information

What We Offer:

  • A culture that celebrates belonging and collaboration, promotes professional development and strives for a work-life balance that supports the team members. Offers flexible work options to support your work and personal needs.
  • Full Benefit Package (Medical, Dental & Vision) that starts your first day.
  • 401k plan with company match, Profit Sharing & Retirement Savings Contribution.
  • Paid Vacation, Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts, among other benefits.

Syngenta has been ranked as a top employer by Science Journal. Learn more about our team and our mission here: https://www.youtube.com/watch?v=OVCN_51GbNI

Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.

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