Responsibilities:

• Work with desk heads, traders and analysts in order to gain understanding of current data flow, data architecture, investment process, and functional requirements for data science analysis.

• Perform time series forecasting & build machine learning models for the European Power, Natural Gas, and Petroleum markets, leveraging historical data to predict future trends.

• Deliver end-to-end data science solutions for users from data ingestion through to production using advanced analytics / machine learning models using both commercial tools and custom coding.

• Apply understanding of the mathematical/statistical fundamentals behind machine learning to improve existing applications and inspire new ones.

• Create new data ingestion pipelines and source new data sets.

• Communicate findings and insights to stakeholders through comprehensive reports and presentations.

• Work closely with our Risk and Commercial investing teams globally to support their data needs.

Qualifications:

• Bachelor's degree in Data Science, Statistics, Computer Science, or a related technical field.

• 2+ years of experience in Data Science role at an energy commodity trading or investment firm, with a focus on European Power, Natural Gas, or Petroleum markets.

• Proven experience with time series forecasting and machine learning techniques, specifically in the energy markets

• Strong programming skills – Python & SQL.

• Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, etc.).

• Excellent problem-solving skills and the ability to work independently and as part of a team.

• Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.