Syngenta Seeds is one of the world’s largest developers and producers of seed for
farmers, commercial growers, retailers and small seed companies. Syngenta seeds
improve the quality and yields of crops. High-quality seeds ensure better and more
productive crops, which is why farmers invest in them. Advanced seeds help mitigate
risks such as disease and drought and allow farmers to grow food using less land, less
water and fewer inputs.

Syngenta Seeds brings farmers more vigorous, stronger, resistant plants, including
innovative hybrid varieties and biotech crops that can thrive even in challenging growing
conditions.

Syngenta Seeds is headquartered in the United States.

Role purpose

As a Data Science Summer Intern, you will support Syngenta’s machine learning applications for plant breeding decision making. You will perform exploratory data science tasks—querying, cleaning, and engineering features from real-world datasets—and build, tune, and evaluate predictive models. You will use Python packages such as LightGBM, XGBoost, sklearn, and pyspark; and write unit tests with pytest and unittest. You will also work with SQL and contribute to code that is tested, maintained, and deployed in a cloud-based production environment. This internship provides the opportunity to apply your analytical and technical skills, collaborate with experienced data scientists, and present your findings to diverse stakeholders.

Accountabilities

• Query, clean, and preprocess large datasets from diverse sources
• Engineer features and build predictive models using LightGBM, XGBoost, sklearn, and pyspark in Python, as well as SQL
• Tune model hyperparameters and evaluate model performance
• Write unit tests for data science and machine learning code using pytest and unittest
• Collaborate in deploying machine learning code to production cloud environments
• Document and present analysis, findings, and recommendations to technical and non-technical audiences
• Work closely with data scientists, engineers, and stakeholders to understand project requirements
• Participate in team meetings and contribute to project planning

Location: Hybrid Role in Durham/Research Triangle Park, NC or Slater, Iowa

Required Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
• Completed coursework in data science, statistics, and linear algebra
• Proficient in Python and SQL for data analysis and modeling
• Experience working with LightGBM, XGBoost, sklearn, pyspark, and pytest
• Experience with data cleaning, feature engineering, and model building
• Strong analytical and problem-solving skills
• Ability to communicate technical concepts clearly
• Enthusiasm for learning and applying new technologies
• Ability to work independently and as part of a team

Preferred Requirements

• Prior experience working with real-world datasets, especially agricultural data
• Coursework or experience in software engineering or database management systems
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for model deployment
• Experience writing unit tests for data science or machine learning code using pytest or unittest
• Previous internship or project experience in applied data science or machine learning
• Experience presenting data science results to diverse audiences

What We Offer:

• A culture that celebrates diversity & inclusion, 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.