Agricultural Data Scientist Job Vacancy in Matsapha, Eswatini – Agriculture Technology

Job Description

Position:Agricultural Data Scientist

Company:John Deere

Location:Matsapha, Eswatini

Experience:3-5 years

Education:Bachelor’s degree in Data Science or related field

Employment Type:Full-time

Industry:Agriculture Technology

Department:Data Science

Salary:SSP 250,000 – 350,000 per annum

Vacancies:1

Company Overview

John Deere is a global leader in agricultural equipment, precision farming solutions, and digital agriculture services. With a strong commitment to sustainability and innovation, John Deere supports farmers worldwide to increase productivity while conserving natural resources. Operating in Eswatini, the company collaborates with local agribusinesses, cooperatives, and research institutions to deliver cutting‑edge technology that drives modern farming practices. As part of its expansion strategy, John Deere is seeking talented professionals to join its data‑driven initiatives, creating new career opportunities for Eswatini residents. This role contributes directly to the company’s mission of advancing agriculture through data, analytics, and intelligent decision‑making, making it an exciting prospect for candidates passionate about both technology and farming.

Job Overview

The Agricultural Data Scientist will design, develop, and implement advanced analytical models that transform raw farm data into actionable insights for John Deere’s customers in Eswatini and the broader Southern African region. Working closely with agronomists, engineers, and product managers, you will leverage machine learning, statistical analysis, and geospatial techniques to optimize crop yields, improve resource efficiency, and support precision agriculture initiatives. This position offers a unique blend of field exposure and cutting‑edge data science, allowing you to influence the future of agriculture in Eswatini while enhancing your professional growth.

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Key Responsibilities

• Collect, clean, and integrate heterogeneous agricultural datasets, including sensor data, satellite imagery, weather records, and farm management logs.
• Develop predictive models for yield forecasting, disease detection, and input optimization using machine learning algorithms.
• Collaborate with agronomy experts to translate domain knowledge into feature engineering and model validation.
• Create interactive dashboards and visualizations that communicate insights to farmers, dealers, and internal stakeholders.
• Implement data pipelines in cloud environments to ensure scalable and reliable analytics delivery.
• Monitor model performance in real‑time, conduct root‑cause analysis, and iterate improvements.
• Contribute to research publications and white papers that showcase John Deere’s innovation in agricultural data science.

Required Skills

• Proficiency in Python or R, with extensive experience in libraries such as pandas, scikit‑learn, TensorFlow, or PyTorch.
• Strong understanding of statistical modeling, time‑series analysis, and geospatial analytics.
• Experience with GIS tools (e.g., QGIS, ArcGIS) and handling raster/vector data.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and data engineering tools (Airflow, Spark).
• Ability to communicate complex technical concepts to non‑technical audiences.
• Knowledge of agronomic practices, crop cycles, and precision farming technologies is a plus.

Education

A minimum of a Bachelor’s degree in Data Science, Computer Science, Statistics, Agronomy, or a related discipline is required. Candidates with a Master’s degree or relevant certifications (e.g., AWS Certified Machine Learning, GIS Professional) will be given preference.

Experience

Applicants should have 3‑5 years of professional experience in data science or analytics, preferably within the agriculture sector or a related field such as environmental science or remote sensing. Demonstrated experience delivering end‑to‑end data solutions in a commercial setting is essential.

Salary

The position offers a competitive salary range of SSP 250,000 to 350,000 per annum, commensurate with experience and qualifications. Performance‑based bonuses and profit‑sharing opportunities may also be available.

Benefits

• Comprehensive health insurance covering medical, dental, and vision.
• Retirement savings plan with company matching contributions.
• Paid parental leave and generous vacation policy.
• Employee assistance program and wellness initiatives.
• Access to John Deere’s global learning platform and professional development resources.

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Training

• On‑boarding program that includes farm field visits and hands‑on training with John Deere’s precision equipment.
• Advanced workshops on machine learning, AI ethics, and geospatial analytics.
• Mentorship pairing with senior data scientists and agronomy experts.
• Opportunities to attend international conferences and industry seminars.

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Working Environment

The role is based in our modern Matsapha office, equipped with state‑of‑the‑art workstations, collaborative spaces, and high‑speed internet connectivity. Frequent field trips to farms and research stations across Eswatini are part of the job, providing a dynamic blend of office and outdoor work. John Deere promotes a culture of safety, inclusivity, and continuous improvement, encouraging employees to share ideas and drive innovation.

Application Process

Interested candidates should submit their updated CV and a cover letter outlining their relevant experience through the online portal on the John Deere careers page. Applications will be reviewed on a rolling basis, and shortlisted candidates will be invited for a virtual interview followed by an on‑site technical assessment.

Equal Opportunity Statement

John Deere is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of gender, race, religion, age, disability, sexual orientation, or any other protected characteristic. All qualified applicants will receive consideration for employment without regard to any such status.