Lead Agricultural Data Scientist

Placements24; Cape Town; Hybrid; ZAR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Annual bonus

Medical aid

Retirement fund

Home office setup allowance

Professional development

Remote team culture

Job summary

Placements24 is seeking an experienced Lead Agricultural Data Scientist to spearhead data-driven initiatives from a remote location across South Africa. You will transform raw agricultural data into actionable insights that optimize crop yields, resource management, and operational efficiency for farms nationwide.

The role requires 7+ years in data science with agricultural applications, expertise in Python or R and ML libraries, and demonstrated leadership in mentoring teams.

Qualifications

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

Responsibilities

• Develop predictive models for crop yield, disease, and resource optimization.
• Lead data mining and statistical analysis of large agricultural datasets.
• Mentor and grow a team of data analysts and scientists.
• Collaborate with agronomists and farm managers to translate business problems into data solutions.

Skills

Python

R

Pandas

Scikit-learn

TensorFlow

PyTorch

SQL

NoSQL

Spark

Hadoop

Leadership

Mentoring

Data mining

Statistics

Experimental design

Education

Master's or Ph.D. in Data Science or related field

Tools

Spark

Hadoop

Git

Job description

About the Role

Our client is seeking an experienced and innovative Lead Agricultural Data Scientist to spearhead data-driven initiatives from a remote location. You will be instrumental in transforming raw agricultural data into actionable insights that optimize crop yields, resource management, and operational efficiency for farms across South Africa. This leadership role involves designing and implementing advanced analytical models, mentoring a team of data analysts, and collaborating with agronomists and stakeholders to drive strategic decision-making. The ideal candidate possesses a strong blend of technical expertise, agricultural domain knowledge, and leadership capabilities, thriving in a collaborative, remote-first environment that values data integrity and impactful results.

Key Responsibilities

• Develop and implement sophisticated predictive models for crop yield forecasting, disease prediction, and optimal resource allocation (water, fertilizer).
• Lead the design and execution of data mining and statistical analysis projects to uncover trends and insights within large agricultural datasets.
• Manage and mentor a team of data analysts and scientists, providing technical guidance and fostering professional growth.
• Collaborate with agronomists, farm managers, and other stakeholders to define analytical requirements and translate business problems into data science solutions.
• Oversee the integration of diverse data sources, including sensor data, satellite imagery, weather data, and historical farm records.
• Present complex findings and recommendations clearly and concisely to both technical and non-technical audiences through compelling visualizations and reports.

Requirements

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Agricultural Engineering, or a related quantitative field.
• Extensive experience (7+ years) in data science, with a significant portion focused on agricultural applications.
• Proficiency in programming languages such as Python or R, and expertise in relevant libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Strong experience with database management (SQL, NoSQL) and big data technologies (e.g., Spark, Hadoop).
• Demonstrated experience in leading data science projects and mentoring team members.
• Excellent understanding of statistical modeling, machine learning algorithms, and experimental design.

Benefits

• Highly competitive salary package with annual bonuses.
• Comprehensive medical aid and retirement fund contributions.
• Generous allowance for home office setup and ongoing remote work expenses.
• Significant opportunities for professional development, attending leading industry conferences, and further education.
• A dynamic and collaborative remote team culture focused on innovation and impact.