Your responsibilities will include:
- Developing, enhancing and productionising machine learning time-series forecasting models, with an initial focus on wind and solar generation.
- Building, automating and maintaining forecasting pipelines to ensure accurate, reliable and timely model outputs for traders.
- Collaborating with data engineering teams to onboard new data feeds, monitor data quality and continuously improve model performance.
- Analysing power market fundamentals and incorporating new features into forecasting models as renewable generation evolves.
- Maintaining dashboards and reports while providing technical modelling support to analysts and key stakeholders.
You will need to have the following:
- A PhD or equivalent advanced qualification in Machine Learning, Data Science, Statistics, Mathematics or another quantitative discipline.
- Experience building and deploying production-grade machine learning models, with a solid understanding of MLOps, Git and CI/CD practices.
- Strong Python programming skills, including experience with Pandas, Scikit-learn and either PyTorch or Keras/TensorFlow.
- Proven experience developing time-series forecasting models, ideally within energy, commodities, financial markets or another data-intensive environment.
- Knowledge of SQL is essential, with experience of Databricks and exposure to energy or commodity trading considered advantageous.
If you're interested in this opportunity, we'd love to hear from you. Please apply today or get in touch with Paula at Marlin Selection.