Quantitative Analyst

Who You Are

We are looking for a highly motivated and innovative Quantitative Analyst to join our team. As a Quantitative Analyst, you will be responsible for developing and implementing advanced trading strategies that leverage your quantitative skills to forecast opportunities and mitigate risks in the energy trading markets.

You will work closely with cross-functional teams to identify and analyze market trends, test new ideas, and execute trades that create value. The ideal candidate will have a passion for data engineering and data science, and a drive to tackle complex problems in the energy market (power or gas).

Job Responsibilities

• Supporting the Quant team with data-related requirements, mainly building data scrapers and ETL pipelines
• Deploying and maintaining solutions in the cloud environment with automated quality checks
• Interacting and contributing to the building of a novel data infrastructure with a timeseries database and large-scale machine learning framework with MLOps best practices
• Focusing on one or more of our two key pillars: quantitative analysis/development or data science
• Contributing to fundamental modelling (auction optimization, fair value models) for the power/gas market
• Building machine learning forecasting models for market fundamentals (renewable production, demand etc.) and contributing to the machine learning framework and MLOps infrastructure.

Skills & Qualifications

• Degree in computer science, physics, maths or related fields
• Fluency in Python (at least 2-3 years in professional setting) with the ability to write clean, modular, well-documented code in a collaborative development setting
• Practical experience in data-engineering workflows like data-scraping, ETL pipelines, job scheduling
• Ability to build, deploy, and maintain a production script in a cloud environment (Azure experience is a plus)
• Familiarity with deployment tools like Docker is a plus
• Familiarity with the data science ecosystem in Python (numpy, pandas, scikit-learn, matplotlib)