Job description

Our client, a pioneering force in agricultural technology, is seeking a talented Agri-Tech Data Scientist to revolutionize farming practices through data-driven insights. This is an on-site role requiring close collaboration with field teams and R&D departments. You will leverage advanced statistical modeling and machine learning techniques to analyze vast datasets from sensors, drones, and satellite imagery to optimize crop yields, resource management, and sustainability efforts. Key responsibilities include: Collecting, cleaning, and pre-processing large, complex agricultural datasets. Developing and implementing predictive models for crop growth, disease detection, and yield forecasting. Designing and executing experiments to test hypotheses and validate model performance. Utilizing geospatial data analysis techniques to map and analyze farm conditions. Collaborating with agronomists and engineers to translate data insights into actionable recommendations for farmers. Building data visualization tools and dashboards to communicate findings effectively to diverse stakeholders. Identifying opportunities for innovation in agricultural processes through data analysis. Evaluating and integrating new data sources and analytical methodologies. Ensuring data integrity, security, and compliance with relevant regulations. Presenting research findings and project outcomes to management and clients. The ideal candidate will hold a Master's or Ph.D. in Data Science, Statistics, Agronomy, Computer Science, or a related quantitative field. A minimum of 4 years of experience in data analysis, with a focus on agricultural applications or environmental science, is required. Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch) are essential. Familiarity with SQL databases and cloud platforms (AWS, Azure, GCP) is expected. Knowledge of GIS software (e.g., ArcGIS, QGIS) and experience with IoT sensor data is highly advantageous. Strong problem-solving abilities and excellent communication skills to convey technical concepts to non-technical audiences are crucial. Join us in shaping the future of sustainable agriculture in Las Vegas, Nevada, US .

Requirements