• PhD with 1 year of experience or MS with 2 years of experience in Data Science, Machine Learning, Statistics, Applied Mathematics, or another highly quantitative discipline.
• Strong Python coding skills for data analysis and modeling, including experience with standard data science packages (numpy, pandas, matplotlib, seaborn, sklearn).
• Demonstrated experience building predictive deep learning, machine learning, simulation, and/or statistical models.
• Ability to learn new quantitative domains and modeling techniques.
• Self-motivated and able to work independently as well as part of a team.
• Strong communication skills for interactions with team members.
• Passion for writing well-structured, well-tested, maintainable, performant, and well-documented code, with an emphasis on scientific code.
• Experience translating scientific models into code.
• Applied experience with agricultural science and/or agricultural datasets.
• Experience using tools for big datasets, such as SQL and PySpark.
• Experience using version control systems, e.g. git.