Remote Agri Data Analyst: Forecast Yields & Optimize Farms

Placements24; Gqeberha; Hybrid; ZAR 420,000 - 680,000; Full time

Benefits offered by this job

Remote work

Performance bonuses

Health insurance

Flexible hours

Paid time off

Job summary

Placements24 is seeking a talented Remote Agricultural Data Analyst to join our innovative team. You will collect, clean, and interpret large agricultural datasets to deliver actionable insights that drive farm profitability and sustainable practices.

You will develop statistical models, create dashboards with Tableau/Power BI, and communicate complex findings to non-technical stakeholders. A strong background in data science and ML is preferred, with excellent collaboration across global teams.

Qualifications

• Degree in data-related field (Data Science, Statistics, Agricultural Science) required.
• Proven experience as Data Analyst, with agricultural data focus.
• Proficiency in Python/R/SQL and data visualization tools.

Responsibilities

• Collect, clean, and process large agricultural datasets.
• Develop statistical models and algorithms to analyze data.
• Forecast yields, identify trends, and assess risks.
• Create reports, dashboards, and visuals for stakeholders.
• Collaborate with agronomists and farm managers to tailor insights.
• Contribute to new data analysis tools and methodologies.

Skills

Python

R

SQL

Excel

Statistics

Machine Learning

Data Visualization

Communication

Education

Bachelor's or Master's in Data Science/Statistics/Agricultural Science or related

Tools

Tableau

Power BI

Job description

Placements24 is seeking a talented Remote Agricultural Data Analyst to join our innovative team. You will collect, clean, and interpret large agricultural datasets to deliver actionable insights that drive farm profitability and sustainable practices.

You will develop statistical models, create dashboards with Tableau/Power BI, and communicate complex findings to non-technical stakeholders. A strong background in data science and ML is preferred, with excellent collaboration across global teams.