- Demonstrated experience in moving and maintaining R&D models to production settings
- MS with 3-4 years of experience in Data Science, Machine Learning, Statistics, Applied Mathematics, or another highly quantitative discipline.
- Demonstrated experience building predictive models using machine learning, deep learning, simulation/process, and/or statistical models.
- Strong Python coding skills for data analysis and modeling, including experience with standard data science packages (numpy, pandas, matplotlib, seaborn, sklearn).
- 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.
- Experience using version control systems like GitHub/GitLab
- PhD with 2+years of experience in Data Science, Machine Learning, Statistics, and/or other highly quantitative discipline.
- 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 with at least one deep learning model (DNN, RNN, etc.) and framework (tensorflow, JAX, pytorch, etc.).
- Experience deploying enterprise-grade packages and models into production pipelines and systems