Remote Agricultural Data Analyst - Yield Prediction & Farm Optimization

Placements24; Soweto; Hybrid; ZAR 550,000 - 900,000; Full time

Benefits offered by this job

Remote work

Competitive salary

Private health insurance

Retirement savings plans

Professional development

Work with cutting-edge data analytics

Job summary

Unknown is seeking a skilled Remote Agricultural Data Analyst to join a globally distributed team. The role focuses on collecting, cleaning, analyzing, and interpreting large agricultural datasets from sensor data, weather, satellites, and equipment logs to drive yield prediction and resource efficiency.

It offers full remote work and impact on farm operations worldwide. The ideal candidate has a Master’s/PhD in a quantitative field, 5+ years in data analysis for agriculture, and strong

Qualifications

• Master's degree or PhD in Data Science, Agricultural Science, Statistics, Computer Science, or a related quantitative field.

Responsibilities

• Collect, process, and cleanse large agricultural datasets from diverse sources to ensure data accuracy and integrity.
• Develop and implement statistical models and machine learning algorithms for yield prediction, crop health monitoring, and resource optimization.
• Analyze spatial and temporal data to identify patterns, trends, and correlations relevant to farm performance.
• Utilize data visualization tools to present complex findings in a clear and understandable manner to stakeholders, including farmers and agronomists.
• Collaborate with software development teams to refine data collection methods and analytical platforms.
• Provide data-driven recommendations to clients for improving irrigation, fertilization, pest management, and other operational strategies.
• Stay updated on the latest advancements in agricultural data analytics, AI, and relevant technologies.
• Document data sources, methodologies, and analytical procedures thoroughly.
• Monitor key performance indicators (KPIs) related to farm output and resource utilization.
• Support the development of predictive analytics tools and reporting dashboards for farm management.

Skills

Data analysis

Statistical modeling

Machine learning

Data mining

GIS and remote sensing knowledge

Python

R

SQL

Tableau

Power BI

Education

Master's degree or PhD in Data Science, Agricultural Science, Statistics, Computer Science, or related quantitative field

Tools

Python

R

SQL

Tableau

Power BI

Matplotlib

Job description

About the Role

Our client, a progressive agricultural technology company, is seeking a skilled Remote Agricultural Data Analyst to join their globally distributed team. This role is entirely remote, offering the flexibility to work from anywhere while contributing to the optimization of farm operations worldwide. The analyst will be responsible for collecting, cleaning, analyzing, and interpreting vast datasets from various agricultural sources, including sensor data, weather patterns, satellite imagery, and farm equipment logs. The primary goal is to provide actionable insights for yield prediction, resource management, and overall farm efficiency improvement. This position is ideal for a data-driven professional with a strong understanding of agricultural principles and advanced analytical capabilities, who thrives in a remote work environment.

Key Responsibilities

• Collect, process, and cleanse large agricultural datasets from diverse sources to ensure data accuracy and integrity.
• Develop and implement statistical models and machine learning algorithms for yield prediction, crop health monitoring, and resource optimization.
• Analyze spatial and temporal data to identify patterns, trends, and correlations relevant to farm performance.
• Utilize data visualization tools to present complex findings in a clear and understandable manner to stakeholders, including farmers and agronomists.
• Collaborate with software development teams to refine data collection methods and analytical platforms.
• Provide data-driven recommendations to clients for improving irrigation, fertilization, pest management, and other operational strategies.
• Stay updated on the latest advancements in agricultural data analytics, AI, and relevant technologies.
• Document data sources, methodologies, and analytical procedures thoroughly.
• Monitor key performance indicators (KPIs) related to farm output and resource utilization.
• Support the development of predictive analytics tools and reporting dashboards for farm management.

Requirements

• A Master's degree or PhD in Data Science, Agricultural Science, Statistics, Computer Science, or a related quantitative field.
• Minimum of 5 years of experience in data analysis, with a significant focus on the agricultural sector.
• Proven expertise in statistical modeling, machine learning techniques, and data mining.
• Proficiency in programming languages commonly used in data science (e.g., Python, R) and SQL.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong understanding of agricultural principles, crop science, and farm operations.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional communication and collaboration skills, adapted for remote team environments.
• Ability to work independently, manage multiple projects, and meet deadlines in a remote setting.
• Experience with GIS and remote sensing data is a plus.

Benefits

• This fully remote position offers a highly competitive salary and a performance-based bonus structure.
• Our client provides a comprehensive benefits package, including private health insurance and retirement savings plans.
• You will have the opportunity to work with cutting-edge data analytics tools and technologies, contributing to significant improvements in global agriculture from your home office.
• Continuous professional development, including access to online training and industry conferences, is encouraged and supported.
• This role offers the flexibility of remote work combined with impactful, data-driven contributions to farm optimization and sustainability.
• Join a dynamic team shaping the future of agricultural intelligence.