Remote Agricultural Data Scientist: AI for Smart Farming

Placements24; LegKraal Gate; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Remote work

Equity options

Professional development budget

Cloud computing resources

Job summary

Placements24 is seeking a Remote Agricultural Data Scientist to drive data-driven insights for agriculture and forestry. Position involves collecting and analyzing diverse data sources, building predictive models, and communicating results to stakeholders across a global team.

The ideal candidate has a strong statistics and ML background, experience with geospatial data, and a passion for applying analytics to sustainable farming.

Qualifications

• Master's or Ph.D. in a quantitative field.
• 4+ years as a Data Scientist applying analytics to real-world problems.
• Proficiency in Python or R with AI/ML libraries.
• Experience with SQL and database management.
• Geospatial data analysis experience is highly desirable.

Responsibilities

• Collect, clean, and analyze large agricultural datasets from sensors, satellite imagery, and weather data.
• Develop, validate, and deploy statistical models and ML algorithms for predictive analytics (yield, disease, planting times).
• Create visualizations and dashboards to communicate findings to technical and non-technical stakeholders.
• Collaborate with agronomists, engineers, and product managers to translate insights into farming solutions.
• Document methodologies and code for reproducibility.

Skills

Python

R

SQL

Pandas

NumPy

Scikit-learn

TensorFlow

Geospatial analysis

Communication

Education

Master's or Ph.D. in Data Science

Tools

ArcGIS

QGIS

Job description

Placements24 is seeking a Remote Agricultural Data Scientist to drive data-driven insights for agriculture and forestry. Position involves collecting and analyzing diverse data sources, building predictive models, and communicating results to stakeholders across a global team.

The ideal candidate has a strong statistics and ML background, experience with geospatial data, and a passion for applying analytics to sustainable farming.