Data Scientist
Core
Develop and deploy machine-learning and AI solutions to improve crop yield, plant quality, and farm productivity using operational, environmental, and image data.
Role type
Senior IC data scientist (computer vision & ML)
Builds
Production-ready ML models, APIs, data pipelines, and dashboards for farm-management and AI platforms
Domain
Agri-tech / Controlled-environment agriculture / Precision farming
Deliverable
production ML models
Required skills
Python, Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, SQL, statistical analysis, feature engineering, model validation
Preferred skills
Computer vision (CNNs, vision transformers, segmentation), time-series forecasting (LSTM), MLOps, Docker, Linux, REST APIs, IoT sensor data processing, cloud platforms (AWS, Azure, GCP), data visualization (Power BI, Grafana, Plotly, Tableau)
Technologies
Python, Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, SQL, Docker, Linux, AWS, Azure, Google Cloud, Power BI, Grafana, Plotly, Tableau
Responsibilities
Develop ML models for yield prediction, growth forecasting, and production planning; Build computer-vision models to measure and identify plant characteristics; Analyze environmental and operational data; Identify relationships between growing conditions and crop quality; Develop anomaly detection and early warning models; Prepare, clean, label, and validate structured, time-series, and image datasets; Design experiments and evaluate model performance; Deploy models and analytical services into farm-management platforms; Develop APIs, data pipelines, and automated reports; Monitor deployed models for accuracy, reliability, and data drift; Collaborate with agronomists to validate findings through farm trials; Maintain documentation for datasets, experiments, and deployment procedures
Seniority
Mid-level, hands-on IC