Remote Agricultural Data Scientist

Placements24; Upington; Hybride; ZAR 900 000 - 1 300 000; Plein temps

Avantages offerts par ce poste

Health, dental, and vision insurance

Fully remote work arrangement

Professional development opportunities

Conference attendance

Résumé du poste

Placements24 is seeking a highly analytical Remote Agricultural Data Scientist to join a forward-thinking team. You will leverage data analysis, machine learning, and statistical modeling to drive innovation in agriculture from a remote location.

Responsibilities include collecting, processing, and interpreting vast agricultural data from sensors, satellite imagery, weather stations, and farm management systems.

Qualifications

• Master's or PhD in Data Science, Statistics, Computer Science, Agricultural Science with a data focus, or related quantitative field.
• Minimum of 5 years of experience as a Data Scientist with agricultural applications.

Responsabilités

• Develop and implement advanced statistical models and ML algorithms for agricultural data.
• Extract, clean, and transform large datasets from sensors, satellite imagery, weather stations, and farm systems.
• Build predictive models for crop yield forecasting, disease detection, and resource optimization.
• Collaborate with agronomists and farm managers to understand data needs and deliver solutions.
• Design experiments to test hypotheses and validate models.
• Ensure data quality, integrity, and security throughout analysis.

Connaissances

Python

R

Data analysis

Statistical modeling

Machine learning

Communication

Formation

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

Outils

SQL

NoSQL

Spark

Hadoop

GIS/Remote Sensing

Description du poste

About the Role

Our client is seeking a highly analytical and skilled Remote Agricultural Data Scientist to join their forward-thinking team. This is a fully remote position where you will leverage your expertise in data analysis, machine learning, and statistical modeling to drive innovation in agriculture. You will be responsible for collecting, processing, and interpreting vast amounts of agricultural data from sources such as sensors, satellite imagery, weather stations, and farm management systems. Your insights will be crucial in developing predictive models for crop yields, optimizing resource allocation (water, fertilizer), identifying disease outbreaks, and enhancing overall farm efficiency and sustainability. The ideal candidate will possess a strong background in data science, a deep understanding of agricultural principles, and the ability to communicate complex findings effectively. This role offers an exceptional opportunity to apply advanced analytical techniques to solve critical challenges in the agricultural sector, working from the convenience of your remote location.

Key Responsibilities

• Develop and implement advanced statistical models and machine learning algorithms to analyze agricultural data.
• Extract, clean, and transform large datasets from diverse sources for analysis.
• Build predictive models for crop yield forecasting, disease detection, and optimal resource management.
• Visualize data and present findings in a clear, concise manner to technical and non-technical stakeholders.
• Identify trends, patterns, and insights within agricultural data to support strategic decision-making.
• Collaborate with agronomists, researchers, and farm managers to understand their data needs and provide solutions.
• Design and conduct experiments to test hypotheses and validate models.
• Stay current with the latest advancements in data science, machine learning, and agricultural technology.
• Ensure data quality, integrity, and security throughout the analysis process.
• Contribute to the development of data-driven tools and platforms for agricultural applications.

Requirements

• A Master's or PhD degree in Data Science, Statistics, Computer Science, Agricultural Science with a data focus, or a related quantitative field.
• Minimum of 5 years of experience as a Data Scientist, with a significant portion focused on agricultural applications or related environmental sciences.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, pandas, NumPy).
• Strong knowledge of statistical modeling, machine learning techniques (regression, classification, clustering), and experimental design.
• Experience with database management (SQL, NoSQL) and data warehousing concepts.
• Ability to work with large, complex datasets and perform data wrangling.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to convey complex technical information clearly.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with GIS and remote sensing data is highly desirable.

Benefits

• A highly competitive salary package and potential for performance-based bonuses.
• Fully remote work arrangement, offering flexibility and work-life balance.
• Comprehensive health, dental, and vision insurance plans.
• Opportunities for continuous professional development, training, and attending conferences.
• Access to state-of-the‑art data science tools and resources.
• The chance to contribute to impactful solutions in sustainable agriculture.