Job description

Basic Qualifications:
  • 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
Preferred Qualifications:
  • 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

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