Job description

Our client is a pioneering force in agricultural technology, seeking a talented and driven Agricultural Data Scientist to join their fully remote team. This role is crucial in leveraging vast datasets to drive innovation and efficiency in modern farming practices. You will be instrumental in developing predictive models, optimizing crop yields, managing resources, and enhancing sustainable agricultural methods. The ideal candidate will possess a strong background in data science, machine learning, statistical analysis, and a genuine passion for agriculture. You will work with diverse data sources, including sensor data, satellite imagery, weather patterns, and soil analyses, to extract actionable insights. This position involves cleaning, transforming, and analyzing complex agricultural data, designing and implementing machine learning algorithms, and collaborating with agronomists, engineers, and other stakeholders to translate data-driven findings into practical solutions. The ability to visualize and communicate complex data findings to both technical and non-technical audiences is paramount. This remote-first position requires a high degree of self-motivation, excellent communication skills, and the ability to work effectively in a distributed team environment. Responsibilities: Collect, clean, and process large datasets from various agricultural sources (sensors, imagery, weather, etc.). Develop, implement, and validate predictive models for crop yield, pest outbreaks, and resource optimization. Apply machine learning and statistical techniques to identify patterns and trends in agricultural data. Design and conduct experiments to test hypotheses and evaluate the impact of different agricultural practices. Develop data visualization tools and dashboards to communicate insights effectively. Collaborate with agronomists and field experts to translate data findings into actionable recommendations. Stay abreast of the latest advancements in data science, machine learning, and agricultural technology. Work with engineering teams to integrate data-driven solutions into existing platforms. Ensure data integrity, quality, and security. Prepare comprehensive reports and presentations on findings and recommendations. Qualifications: Master's or Ph.D. in Data Science, Statistics, Computer Science, Agricultural Science, or a related quantitative field. Minimum of 5 years of experience as a Data Scientist or in a similar analytical role. Strong proficiency in programming languages such as Python or R. Experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Expertise in statistical analysis and experimental design. Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP) is a plus. Familiarity with agricultural data and practices is highly desirable. Excellent data visualization skills. Strong problem-solving abilities and critical thinking. Effective communication and collaboration skills, with the ability to explain complex concepts to diverse audiences. This role offers the chance to make a tangible impact on the future of agriculture, contributing to more sustainable and efficient food production.

Requirements