Job Description

Our Global Commodity Analysis team is looking for YOU!
Our Global Commodity Analysis team is looking for YOU!

Your responsibilities

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Supporting analytical activities with respect to the ammonia market. Design and implement a real-time data pipeline to feed the model with live inputs from relevant data sources. Work on and enhance the existing ML forecasting model, and implement additional algorithms (e.g., LSTMs, GRUs, Transformer-based models) on Databricks to improve performance and accuracy. Integrate the model output into a production-ready environment, ensuring reliability and maintainability. Document code, methodologies, findings, and improvements. Stay updated on the latest advancements in machine learning, time series forecasting, and MLOps.

Your profile

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Currently enrolled as a master’s student in Computer Science, Data Science, Artificial Intelligence, Energy Economics, Energy Engineering, or another related technical or quantitative field. Strong programming skills in Python, including experience with data science libraries (pandas, NumPy, matplotlib, seaborn), and machine learning frameworks (scikit-learn, PyTorch, TensorFlow). A solid understanding of ML workflows, including data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, is a must. Familiarity with Databricks and Apache Spark (or similar cloud-based ML platforms) for data processing and pipeline development is a big advantage. Some previous experience in time series forecasting or predictive modelling. Basic knowledge of data engineering concepts, including building and maintaining data pipelines. * Strong analytical mindset with the ability to work independently and collaboratively.