Agronomic Data Science & Engineering Intern

Description

Join a fast-paced research & development team that is using leading edge technologies to advance software-based agronomic solutions for growers around the globe. As an intern at Corteva, you will have a unique opportunity to learn, grow, and expand your knowledge as you help research and develop the digital crop advisor of tomorrow. Experience developing software with Python is essential for this position. Applicants should also have a drive for excellence, excel in using creative approaches to solving complex problems, and possess an innovative mindset. Strong applicants will have completed courses or projects involving data science and/or statistical analysis and modelling. Affinity with agriculture and biological systems is an advantage.

What Youll Do:

Model, integrate, and analyze agricultural and weather data

Projects in relation to plant disease and pest management modeling in crops such as corn, soybeans and canola, etc

Develop and execute Python code in high performance distributed Unix/Linux computing environments

Work collaboratively on agile research teams to create innovative software solutions for growers

Design, develop, and support a variety of high-performance software solutions for R&D

Continuously learn and share your technical knowledge with key leaders and project stakeholders

Qualifications

What Youll Bring:

Current enrollment in a masters or doctoral degree program in mathematics, statistics, plant pathology, data science, computer science or related agricultural engineering field.

Must be enrolled in classes the semester following their internship with Corteva at a US-accredited institution.

3.0 current cumulative GPA

Must be able to work full-time (40 hours per week) in Indianapolis, IN for 10-12 weeks during the duration of the internship (typically May to August).

Excellent problem-solving skills using creative approaches

Hands-on experience with Python and data analysis/statistics is required

Relevant experience using machine learning and mechanistic modelling approaches to solve complex problems with mixed variable datasets

Ability to work effectively with cross-functional science and engineering teams and business partners

Not required, but preferred technology experiences: Numpy, Pandas, Sklearn, TensorFlow, keras, Matplotlib, Kubernetes, Amazon Web Services (AWS), RESTful API Services

Corteva Agriscience™ is an equal opportunity employer. We are committed to boldly embracing the power of inclusion, diversity, and equity to enrich the lives of our employees and strengthen the performance of our company, while advancing equity in agriculture. Qualified applicants will be considered without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability or any other protected class. Discrimination, harassment and retaliation are inconsistent with our values and will not be tolerated. If you require a reasonable accommodation to search or apply for a position, please visit:

Accessibility Page for Contact Information

For US Applicants: See the ‘Equal Employment Opportunity is the Law’ poster

To all recruitment agencies: Corteva does not accept unsolicited third party resumes and is not responsible for any fees related to unsolicited resumes.