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Our mission at Energetech is to accelerate the global path towards the green transition. We are an energy trading company that brings together the best talent from around the world to reinvent the way energy flows through global markets.

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)