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.