Data Scientist / Senior Data Scientist

Role Overview: You will perform data analysis on crop, greenhouse gas (GHG), and spatial datasets to support scientific research and decision-making. You will conduct statistical analysis and develop methodologies to enhance research outcomes. Additionally, you will support running and calibrating crop models, analyzing model outputs, and developing, automating, and maintaining data processing and analysis pipelines for large-scale datasets. Your role will also involve designing and implementing visualization tools, dashboards, and analytical platforms to support the Science team. Furthermore, you will apply machine learning (ML) and deep learning (DeepML) techniques for predictive modeling, pattern recognition, and optimization. You will also utilize generative AI (GenAI) techniques to support data extraction, synthesis, and augmentation. Collaboration with scientists, engineers, and stakeholders to translate research questions into actionable insights will be an essential aspect of your responsibilities. Finally, you will contribute to research publications, technical documentation, and reports. Key Responsibilities: - Perform data analysis on crop, greenhouse gas (GHG), and spatial datasets - Conduct statistical analysis and develop methodologies - Support running and calibrating crop models and analyzing model outputs - Develop, automate, and maintain data processing and analysis pipelines for large-scale datasets - Design and implement visualization tools, dashboards, and analytical platforms - Apply machine learning (ML) and deep learning (DeepML) techniques - Utilize generative AI (GenAI) techniques - Collaborate with scientists, engineers, and stakeholders - Contribute to research publications, technical documentation, and reports Qualifications: - A degree in Data Science, Computer Science, Environmental Science, Agronomy, or a related field - Proficiency in programming languages such as Python or R for data analysis and modeling - Ability to automate workflows and develop scalable data pipelines - Strong analytical and problem-solving skills with attention to detail - Effective communication skills and ability to work collaboratively in an interdisciplinary team Preferred Qualifications: - Experience working with geospatial datasets and GIS tools (e.g., QGIS, GDAL, Google Earth Engine) - Strong background in statistical modeling and data visualization - Experience with ML/DeepML techniques and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) - Familiarity with generative AI concepts and applications - Familiarity with crop/GHG modeling Additional Information: Join a small, ambitious, and international team and enjoy the following benefits: - Competitive salary and benefits package (ESOP) - Key role in shaping a fast-growing climate tech startup - Support for learning & professional development - A culture of undogmatic, unbureaucratic creativity and collaboration (Note: The additional information section has been included in the job description as it provides insights into the company's culture and benefits for the employee.) Role Overview: You will perform data analysis on crop, greenhouse gas (GHG), and spatial datasets to support scientific research and decision-making. You will conduct statistical analysis and develop methodologies to enhance research outcomes. Additionally, you will support running and calibrating crop models, analyzing model outputs, and developing, automating, and maintaining data processing and analysis pipelines for large-scale datasets. Your role will also involve designing and implementing visualization tools, dashboards, and analytical platforms to support the Science team. Furthermore, you will apply machine learning (ML) and deep learning (DeepML) techniques for predictive modeling, pattern recognition, and optimization. You will also utilize generative AI (GenAI) techniques to support data extraction, synthesis, and augmentation. Collaboration with scientists, engineers, and stakeholders to translate research questions into actionable insights will be an essential aspect of your responsibilities. Finally, you will contribute to research publications, technical documentation, and reports. Key Responsibilities: - Perform data analysis on crop, greenhouse gas (GHG), and spatial datasets - Conduct statistical analysis and develop methodologies - Support running and calibrating crop models and analyzing model outputs - Develop, automate, and maintain data processing and analysis pipelines for large-scale datasets - Design and implement visualization tools, dashboards, and analytical platforms - Apply machine learning (ML) and deep learning (DeepML) techniques - Utilize generative AI (GenAI) techniques - Collaborate with scientists, engineers, and stakeholders - Contribute to research publications, technical documentation, and reports Qualifications: - A degree in Data Science, Computer Science, Environmental Science, Agronomy, or a related field - Proficiency