Sr. Data Scientist for Whippany, NJ to develop, implement & deploy machine learning and AI models to lead and oversee pricing and demand forecasting projects for crop science products; lead & organize code reviews; develop reports on model inputs & outputs, use cases and product performance; lead the communication of modeling predictions, results & recommendations to internal stakeholders; provide technical direction on test design, research formulation & model validation; mentor & train junior data scientists. Requires Master's in Data Science, Applied Mathematics, Statistics or closely related quantitative field & 1 yr experience using machine learning and/or deep learning algorithms in Python and R with agronomic, biotech and/or environmental data to contribute to product demand forecasting, pricing, elasticity estimation and/or competitor simulation; applying Copula Theory to identify & analyze spatial and temporal data correlations; assisting in developing discrete choice & causal inference models, including logit, nested logit, mixed logit, BLP, instrumental variables and/or fixed-effect models, for modeling and utilization of agronomic, biotech and/or environmental data; using XGBoost & NGBoost to participate in sales forecasting & feature engineering; using SHAP for model interpretation; performing code review using GitHub for version control; using automatic hyperparameter tuning tools, including Optuna, to fine-tune models; contributing to deploying code into a production environment using a scalable cloud-based platform, including AWS and/or Domino; and assisting in querying data from GCP using BigQuery. Telecommuting permitted.