Hybrid Agricultural Data Analyst: Optimize Yields

Placements24; Noord-Kaap; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Professional development

Flexible hours

Hybrid work model

Job summary

Placements24 is seeking an Agricultural Data Analyst to join our client in Kimberley, Northern Cape. You will collect, clean, analyze, and interpret agricultural data to support decision-making, improve efficiency, and promote sustainable farming practices.

The role emphasizes hybrid collaboration and independent work. You will work with Python/R, SQL, and visualization tools to uncover trends, build models, and deliver insights for better crop yields and resource management.

Qualifications

• Bachelor's or Master's in a quantitative field.
• Minimum 4 years as a Data Analyst in agricultural/biological data.
• Proficiency in Python or R and SQL.
• Experience with Tableau/Power BI for dashboards.
• Strong analytical and communication skills.

Responsibilities

• Collect, clean, and process large datasets from agricultural sources (sensors, imagery, farm software).
• Perform statistical analysis to identify trends and correlations in agricultural data.
• Develop data models and algorithms to predict yields and optimize resources.
• Create data visualizations and dashboards to communicate findings to stakeholders.
• Provide actionable insights to agronomists, farm managers, and executives.
• Collaborate with IT to enhance data infrastructure and analytical tools.

Skills

Python

R

SQL

Tableau

Power BI

Matplotlib

Statistics concepts

Communication skills

Problem solving

Education

Bachelor's degree in Data Science

Master's degree in Data Science

Bachelor's degree in Agricultural Science

Tools

Tableau

Power BI

Matplotlib

Job description

Placements24 is seeking an Agricultural Data Analyst to join our client in Kimberley, Northern Cape. You will collect, clean, analyze, and interpret agricultural data to support decision-making, improve efficiency, and promote sustainable farming practices.

The role emphasizes hybrid collaboration and independent work. You will work with Python/R, SQL, and visualization tools to uncover trends, build models, and deliver insights for better crop yields and resource management.