Agricultural Data Scientist - Precision Farming

Placements24; Pretoria; Hybride; ZAR 700 000 - 1 000 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Healthcare coverage

Remote work flexibility

Professional development

Résumé du poste

Placements24 is seeking an Agricultural Data Scientist in Pretoria. This remote-first role focuses on collecting, processing, and analyzing large agri datasets from sensors, drones, satellites, and yield monitors.

You will build predictive models to optimize yields and resources while translating insights for agronomists and farm managers. You will collaborate with engineers and researchers to deploy data pipelines, evaluate farming practices, and contribute to data-driven product development in

Qualifications

• Master's or PhD in a data-related field with agricultural relevance.

Responsabilités

• Design and implement data collection strategies for agricultural operations.

Connaissances

Python

R

pandas

NumPy

scikit-learn

TensorFlow

SQL

NoSQL

Cloud platforms

Formation

Master's or PhD in Data Science/Statistics/CS/Agri-Science

Outils

SQL

NoSQL

Data warehousing

AWS

Azure

GCP

Description du poste

About the Role

Our client is at the forefront of agricultural innovation and is seeking a talented Agricultural Data Scientist to join their team based in Pretoria . This is a remote-first position, allowing you to leverage your data analysis skills to drive advancements in precision farming. You will be responsible for collecting, processing, and analyzing vast datasets generated from various agricultural sources, including sensors, drones, satellite imagery, and yield monitors. Your insights will be critical in developing predictive models, optimizing resource allocation, and improving crop management strategies. This role is ideal for a data-driven professional passionate about transforming agriculture through technology and sustainable practices. You will collaborate closely with agronomists, engineers, and farm managers to translate complex data into actionable intelligence.

Key Responsibilities

• Design and implement data collection strategies for agricultural operations.
• Clean, transform, and manage large, complex datasets from diverse agricultural sources.
• Develop and deploy statistical models and machine learning algorithms for yield prediction, disease detection, and resource optimization.
• Visualize data and communicate findings effectively to technical and non-technical audiences.
• Collaborate with agronomists and farm managers to translate data insights into practical farming recommendations.
• Evaluate the effectiveness of different farming practices and technologies based on data analysis.
• Develop and maintain data pipelines and automated reporting systems.
• Stay current with advancements in data science, machine learning, and agricultural technology.
• Contribute to the development of new data-driven products and services for the agricultural sector.

Requirements

• Master's or PhD degree in Data Science, Statistics, Computer Science, Agricultural Science with a data focus, or a related quantitative field.
• Proven experience as a Data Scientist, with a portfolio demonstrating successful projects.
• Strong proficiency in programming languages such as Python or R, and relevant libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow).
• Experience with database management (SQL/NoSQL) and data warehousing concepts.
• Familiarity with cloud computing platforms (AWS, Azure, GCP) is a plus.
• Understanding of agricultural principles, crop science, and precision farming techniques is highly desirable.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain complex technical concepts clearly.
• Ability to work independently and collaboratively in a remote team environment.

Benefits

• Highly competitive annual salary of Rands .
• Comprehensive healthcare coverage.
• Remote work flexibility, allowing for a strong work-life balance.
• Professional development opportunities, including training and conference attendance.
• Access to state-of-the‑art data analytics tools and infrastructure.
• Opportunity to work on impactful projects that advance sustainable agriculture.
• A collaborative and innovative team culture.