Remote Agricultural Data Analyst

Placements24; Pretoria; Hybrid; ZAR 350,000 - 550,000; Full time

Benefits offered by this job

Competitive salary and remote benefits

Leading-edge agricultural technology

Flexible working hours

Continuous learning and development

Impact on sustainable agriculture

Job summary

Placements24 is seeking a Remote Agricultural Data Analyst to join an innovative team. In this fully remote role, you will collect, process, and analyze large agricultural datasets to derive actionable insights for optimizing farm operations, improving yields, and promoting sustainability.

You will collaborate with agronomists, farmers, and engineers to translate complex data into practical recommendations.

Qualifications

• Bachelor's or master's degree in data-related field.
• Experience as data analyst, preferably with agricultural data.
• Proficiency in Python or R and SQL.
• Experience with Tableau/Power BI and statistical software.
• Strong analytical and communication skills; ability to work remotely.

Responsibilities

• Collect and clean agricultural datasets from sensors, satellite imagery, and farm management software.
• Develop statistical models and machine learning algorithms to identify trends and correlations in agricultural data.
• Generate reports, dashboards and visualizations to communicate findings to stakeholders.
• Collaborate with agronomy teams to validate insights and support decision-making.
• Identify opportunities to improve data collection methods and analytics processes.
• Stay current with advancements in data analytics and agricultural technology.

Skills

Python

SQL

R

Data Visualization

Communication

Remote work

Education

Bachelor's or Master's in data science / statistics / agricultural science / CS

Tools

Tableau

Power BI

SQL

Job description

About the Role

Our client is looking for a skilled Remote Agricultural Data Analyst to join their innovative team. In this fully remote position, you will be responsible for collecting, processing, and analyzing vast amounts of agricultural data to provide actionable insights for optimizing farm operations, improving crop yields, and enhancing sustainability. You will work with cutting-edge technologies and collaborate with agronomists, farmers, and engineers to translate complex data into clear, practical recommendations. This role is ideal for a data-driven professional passionate about the intersection of technology and agriculture.

Key Responsibilities

• Collect, clean, and organize agricultural datasets from various sources, including sensors, satellite imagery, and farm management software.
• Develop and implement statistical models and machine learning algorithms to identify trends, patterns, and correlations in agricultural data.
• Generate reports, dashboards, and visualizations to communicate findings and recommendations to stakeholders.
• Collaborate with agronomy teams to validate data insights and support decision-making processes.
• Identify opportunities to improve data collection methods and analytical processes.
• Stay current with advancements in data analytics, agricultural technology, and relevant software tools.

Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Agricultural Science, Computer Science, or a related quantitative field.
• Proven experience as a Data Analyst, with a focus on agricultural data is a strong plus.
• Proficiency in data analysis languages such as Python or R, and SQL.
• Experience with data visualization tools (e.g., Tableau, Power BI) and statistical software.
• Strong understanding of agricultural principles and practices is highly desirable.
• Excellent analytical, problem-solving, and communication skills, with the ability to work effectively remotely.

Benefits

• Competitive salary and comprehensive remote work benefits.
• Opportunity to work with leading-edge agricultural technology.
• Flexible working hours and a supportive remote team environment.
• Continuous learning and professional development opportunities.
• Make a tangible impact on sustainable agriculture through data-driven insights.