Remote Agricultural Data Scientist - Farm Analytics Lead

Placements24; Randburg; Hybrid; ZAR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Fully remote

Professional development budget

Job summary

Placements24 is seeking a highly skilled Remote Agricultural Data Scientist to join its global team. You will develop advanced analytical models leveraging data from IoT sensors, satellite imagery, and farm management systems to optimize crop yields and farm operations, with impact across Randburg, Gauteng, and beyond.

You will lead data-driven initiatives, design predictive solutions, and present insights to both technical and non-technical stakeholders while collaborating with a global team.

Qualifications

• Master's degree or Ph.D. in Data Science, Statistics, Computer Science, Agricultural Science (with a strong quantitative focus), or a related field.
• Minimum of 6 years of experience in data science, with a proven track record of applying advanced analytical techniques to real-world problems.
• Proficiency in Python or R and libraries like scikit-learn, TensorFlow, PyTorch, Pandas.
• Strong knowledge of SQL and NoSQL and data warehousing concepts.
• Experience with machine learning algorithms (regression, classification, clustering, deep learning) and statistical modeling.
• Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies.
• Understanding of agricultural principles, crop science, or farm management is highly desirable.
• Excellent problem-solving, analytical, and communication skills.

Responsibilities

• Design, develop, and implement predictive models and algorithms for agricultural applications.
• Analyze large datasets from on-farm sensors, drones, satellite imagery, weather stations, and farm management software.
• Develop KPIs and dashboards to track farm performance and identify improvements.
• Translate data insights into actionable recommendations for farmers and agronomists.
• Collaborate remotely with engineers, agronomists, and product managers.
• Conduct exploratory data analysis to uncover patterns and correlations in agricultural data.
• Optimize models for accuracy, scalability, and efficiency.
• Stay abreast of advances in data science and agricultural tech.

Skills

Data science

Machine learning

Statistics

Python

R

SQL

NoSQL

Cloud computing

Big data

Education

Master's degree in Data Science

PhD in a related field

Tools

scikit-learn

TensorFlow

PyTorch

Pandas

Job description

About the Role

Our client, a global leader in AgTech innovation, is seeking a highly skilled Remote Agricultural Data Scientist to join their dynamic and fully remote team. This position is instrumental in harnessing the power of big data to drive insights and improvements in farm operations, crop management, and yield optimization. You will be responsible for developing advanced analytical models, interpreting complex datasets from various agricultural sources (including IoT sensors, satellite imagery, and farm management systems), and translating these findings into actionable strategies for clients worldwide, with a focus on enhancing productivity in regions like Randburg, Gauteng, ZA. The ideal candidate possesses a strong quantitative background, expertise in machine learning and statistical modeling, and a passion for applying these skills to solve real-world agricultural challenges. This is a unique opportunity to shape the future of data-driven farming from a remote location.

Key Responsibilities

• Design, develop, and implement predictive models and algorithms using machine learning and statistical techniques for agricultural applications.
• Analyze large and diverse datasets from on-farm sensors, drones, satellite imagery, weather stations, and farm management software.
• Develop key performance indicators (KPIs) and dashboards to track farm performance and identify areas for improvement.
• Translate complex data insights into clear, actionable recommendations for farmers, agronomists, and other stakeholders.
• Collaborate remotely with cross-functional teams, including software engineers, agronomists, and product managers.
• Conduct exploratory data analysis to uncover patterns, trends, and correlations in agricultural data.
• Optimize existing models and algorithms for accuracy, scalability, and efficiency.
• Stay abreast of the latest advancements in data science, machine learning, and agricultural technologies.
• Ensure data quality, integrity, and security throughout the analytical process.
• Present findings and recommendations to both technical and non-technical audiences.

Requirements

• A Master's degree or Ph.D. in Data Science, Statistics, Computer Science, Agricultural Science (with a strong quantitative focus), or a related field.
• Minimum of 6 years of experience in data science, with a proven track record of applying advanced analytical techniques to real-world problems.
• Expertise in programming languages such as Python or R, and proficiency with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
• Strong knowledge of database management (SQL, NoSQL) and data warehousing concepts.
• Experience with machine learning algorithms (regression, classification, clustering, deep learning) and statistical modeling.
• Familiarity with cloud computing platforms (AWS, Azure, GCP) and big data technologies.
• Understanding of agricultural principles, crop science, or farm management is highly desirable.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, essential for effective remote teamwork.
• Ability to work independently and manage multiple projects effectively.

Benefits

This is a fully remote position, offering flexibility and work-life balance. Our client provides a competitive salary, comprehensive health and retirement benefits, and a significant budget for professional development, conferences, and training. You will have the opportunity to work on impactful projects that are shaping the future of agriculture, collaborating with a global team of experts. Access to state-of-the-art analytical tools and platforms is provided, with a particular focus on improving agricultural outcomes in Randburg, Gauteng, ZA region.