Remote Agricultural Data Scientist for Yield & Insights

Placements24; East London; À distance; ZAR 600 000 - 900 000; Plein temps

Résumé du poste

Placements24 is seeking an Agricultural Data Scientist to transform vast agricultural data into actionable insights. The role is remote, supporting decision-making for farm operations, crop productivity, and sustainability by leveraging data from sensors, drones, and satellite imagery.

The ideal candidate will have a strong background in statistical modeling, machine learning, and data visualization, and will collaborate with agronomists to define KPIs and create data-driven recommendations

Qualifications

• Strong background in statistical modeling, machine learning, and data visualization.

Responsabilités

• Collect, clean, and preprocess large datasets from diverse agricultural sources.
• Develop and apply statistical models and machine learning algorithms to analyze agricultural data, identify patterns, and predict trends (e.g., yield prediction, disease outbreak forecasting).
• Design and implement experiments to test hypotheses and validate models.
• Create compelling data visualizations and dashboards to communicate complex findings to technical and non-technical stakeholders.
• Collaborate with agronomists and domain experts to define key performance indicators (KPIs) and analytical requirements.
• Develop data-driven recommendations for optimizing farming practices, resource allocation, and crop management strategies.
• Contribute to the development of new data products and analytical tools for the agricultural industry.
• Stay current with the latest advancements in data science, machine learning, and their applications in agriculture.
• Ensure data integrity, security, and compliance with relevant privacy regulations.
• Work independently and effectively within a remote team structure.

Description du poste

Placements24 is seeking an Agricultural Data Scientist to transform vast agricultural data into actionable insights. The role is remote, supporting decision-making for farm operations, crop productivity, and sustainability by leveraging data from sensors, drones, and satellite imagery.

The ideal candidate will have a strong background in statistical modeling, machine learning, and data visualization, and will collaborate with agronomists to define KPIs and create data-driven recommendations