Remote Agricultural Data Scientist - Forecasting & Insights

Placements24; United States; Remote; USD 130,000 - 170,000; Full time

Benefits offered by this job

Remote-friendly

Competitive salary

Performance bonuses

Learning resources

Job summary

Placements24 is seeking a Remote Agricultural Data Scientist to analyze large datasets from sensors, weather, soil, and yields, delivering actionable insights to farmers. The role is remote from the United States with a programmatic focus on South Africa's Paarl region.

You will build models, run experiments, visualize results, and collaborate with product teams to embed data-driven capabilities in agricultural platforms while staying current with advances in data science and agronomy.

Qualifications

• Advanced degree with 5+ years in data science in agriculture is expected.
• Proficient in Python or R with ML libraries.
• Experience with SQL/NoSQL and data warehousing.

Responsibilities

• Collect, preprocess, and quality-check diverse agricultural datasets.
• Develop statistical models and ML algorithms to forecast yield and disease risk.
• Design A/B tests and experiments to evaluate farming strategies and technologies.
• Create dashboards and reports to communicate findings to farmers and agronomists.
• Collaborate with product teams to embed data-driven insights into platforms.
• Stay updated on advances in data science and agriculture.

Skills

Python

R

Statistical modeling

ML techniques

Experiment design

Data visualization

Education

Master's/PhD in Data Science or related

Tools

TensorFlow

scikit-learn

Pandas

SQL

NoSQL

Job description

Placements24 is seeking a Remote Agricultural Data Scientist to analyze large datasets from sensors, weather, soil, and yields, delivering actionable insights to farmers. The role is remote from the United States with a programmatic focus on South Africa's Paarl region.

You will build models, run experiments, visualize results, and collaborate with product teams to embed data-driven capabilities in agricultural platforms while staying current with advances in data science and agronomy.