Full-Time Senior Machine Learning Scientist

• Designing and implementing innovative machine learning solutions to solve complex agricultural and environmental challenges.
• Developing and optimizing predictive models using structured historical cross-functional data from field trials, laboratory experiments, and environmental measurements.
• Translating agricultural/environmental problems into data science solutions in collaboration with domain experts.
• Supporting experimental design to ensure data suitability for modeling purposes.
• Working with IT teams on end-to-end ML projects from data preparation to model deployment and monitoring.
• Presenting insights and recommendations to stakeholders across different functions.
• Engaging with high-priority digital transformation projects to understand opportunities to accelerate the impact of data science for predictive field trialing.

• PhD in Computer Science, Data Science, Machine Learning, or related field (or M.Sc. with extensive hands-on ML experience).
• Proven experience in developing machine learning models, particularly:Supervised learning (Random Forests, XGBoost, SVM etc.).
• Clustering and dimensionality reduction.
• Time series analysis.
• Handling hierarchical/nested data structures.
• Strong programming skills in Python and experience with ML frameworks (scikit-learn, pandas, etc.).
• Demonstrated ability to develop novel solutions beyond applying existing frameworks.
• Creative problem-solving mindset and ability to think outside standard approaches.
• Experience in adapting and modifying algorithms to suit specific problem requirements.
• Passion for emerging technologies, including Generative AI and other innovative approaches.
• Strong communication skills to explain technical concepts to non-technical stakeholders.
• Ability to visualize and story-tell with data to communicate results to parties with varying levels of technical proficiency.
• Interest in agriculture, environmental science, or related fields.

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