Unlocking the full potential of forests, both ecologically and emotionally. We are seeking a highly skilled Senior Data Scientist to join our team. The successful candidate will design and implement advanced analytical models, leveraging geospatial and temporal data, with a focus on multi-objective optimization, simulations, and large language models (LLMs). This role is ideal for a technical expert passionate about applying sophisticated data science techniques to solve complex, time-sensitive, and spatially aware challenges. Key Responsibilities: Develop and deploy machine learning models, emphasizing simulations and AI-powered recommender systems, to tackle business and research challenges. Analyze geospatial data to uncover spatial trends and relationships, integrating temporal data for dynamic, real-world insights. Model temporal data for applications like forecasting, trend detection, using techniques such as LSTMs or transformers. Extract meaningful patterns from large, complex datasets using statistical methods and advanced data processing techniques. Train and optimize models (e.g., transformers, classifiers, encoders, LLMs) using TensorFlow or PyTorch to enhance AI solutions. Fine-tune LLMs for tasks like text generation, classification, or semantic analysis. Collaborate with engineering teams to deploy scalable models into production environments. Qualifications: Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. 4 years of experience in data science, with hands-on expertise in the training, optimizing and evaluating AI-powered models. Proficiency in TensorFlow and/or PyTorch for building and deploying deep neural networks. Experience with large language models (e.g., BERT, or custom implementations) and their applications. Strong skills in Python and libraries such as NumPy, pandas, and scikit-learn for data manipulation and modeling. Hands-on experience in modeling temporal data (e.g., time-series analysis, sequential modeling). Solid understanding of statistical modeling, multi-objective optimization techniques, and neural network architectures. Preferred Skills: Demonstrated ability to process and analyze geospatial data using tools like GeoPandas, GDAL. Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for managing large-scale data and models. Experience with GIS systems or geospatial visualization tools (e.g., QGIS, Mapbox). Background in deploying models at scale using containerization (e.g., Docker) or orchestration tools. Interested? If you would like to become part of our team and work towards a sustainable future, we look forward to receiving your application We look forward to getting to know you. About us At Tree.ly, we are fully committed to climate protection and enhance the importance of forests as critical ecosystems through innovative business models. We connect companies and forest owners to sustainably and climate-resiliently manage forests through direct investments. Our vision is to create a future where forests are valued for their ecological services and managed sustainably in alignment with business interests.