At a Glance
- Tasks: Develop and enhance machine learning models for trading decisions in European power markets.
- Company: Leading commodity trading firm based in London with a focus on innovation.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on renewable energy and data-driven decision making.
- Why this job: Make a real impact on trading performance while working with cutting-edge technology.
- Qualifications: PhD or equivalent in a quantitative field and strong Python programming skills.
The predicted salary is between 60000 - 80000 £ per year.
Our client, a leading commodity trading firm, is looking for a Power Analyst – Data Scientist to join their team in London.
This is an exciting opportunity to develop and enhance machine learning forecasting models that support trading decisions across European power markets.
Working closely with traders, analysts and data teams, you will help improve forecasting accuracy and contribute directly to trading performance.
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 Ph D 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 Py Torch or Keras/Tensor Flow.
- 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.
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Power Data Scientist employer: Marlin Selection Recruitment
Join a dynamic and innovative Commodity Trading firm in London, where you will be part of a collaborative team dedicated to excellence in trade operations. The company offers a supportive work culture that prioritises employee growth through continuous learning opportunities and mentorship, ensuring you can advance your career while making a meaningful impact in the energy sector. With competitive benefits and a focus on work-life balance, this is an excellent opportunity for those looking to thrive in a fast-paced environment.
Contact Details:
Marlin Selection Recruitment Recruitment Team
