Intern – Machine Learning, Data Science & Software Development
TotalEnergiesJobsCloseBy Editorial Insights
TotalEnergies seeks an Intern in Machine Learning, Data Science and Software Development in Geneva to join the ML Modelling & Delivery team for Algo Strategies in Trading onsite in the Geneva WTC1. You will help develop short-term power algorithmic trading models, integrate new data sources, engineer features, train and backtest ML models, contribute to portfolio construction and risk management, and help build robust trading tools in a fast evolving market. Ideal candidates are pursuing a Master’s degree in a quantitative field, proficient in Python, and familiar with Scikit-learn, XGBoost or TensorFlow. To apply, tailor your CV to ML projects and data pipelines, include any trading or energy-market experience, provide links to GitHub, and demonstrate teamwork and curiosity in English.
Context & Environment
TotalEnergies has developed a strong expertise in oil and biofuels, natural gas and electricity trading. Trading entities are based in Geneva, Paris, Houston and Singapore.
TotalEnergies installed its European trading hub across in Geneva, which now bring together very large teams around trading activities: TotalEnergies Trading & Shipping (T&S) and TotalEnergies Gas and Power (TGP).
TotalEnergies Gas and Power (TGP) is the trading arm of TotalEnergies in the field of low carbon energies. As such, it operates in fast-evolving market dynamics influenced by internal and external factors that require constant adaptation and evolution.
The Trading division in Geneva is responsible for optimising the purchase & sales portfolios of gas, electricity, CO2 emissions, dry bulk, and LNG in all recognised markets worldwide, in compliance with the Company trading guidelines.
In such context, TGP helps to ensure growth and profitability to a key segment of the business in order to reach the objective of Carbon Neutrality by 2050.
Based in Geneva, the ML Modelling & Delivery team within the Algo Strategies for Trading group develops machine learning solutions and software tools that support trading desks in their decision-making. The team works in a fast-moving environment shaped by evolving market dynamics, climate policies and the transformation of the energy sector.
This internship offers a unique opportunity to apply machine learning, data science and software development in a real-world trading environment, contributing to practical tools and models used by business teams.
Activities
What you will do
As an intern, you will contribute to the development of short-term power algorithmic trading strategies based on machine learning models.
Depending on the team’s priorities and your profile, your responsibilities may include:
- Developing a solid understanding of European power markets, including their structure and short-term dynamics
- Integrating new data sources, including market, fundamental or alternative data, into existing modelling pipelines
- Performing feature engineering to identify relevant signals from newly integrated data
- Designing, training and evaluating machine learning models using AutoML libraries and other ML frameworks
- Backtesting predictive models and algorithmic trading strategies
- Contributing to portfolio construction and risk management approaches
- Monitoring and analysing model performance in paper trading and production environments
- Supporting the development of robust, reusable software tools for trading and modelling activities
Candidate Profile
What we are looking for
You are currently pursuing a Master’s degree in Computer Science, Data Science, Mathematics, Physics, Engineering or a related quantitative field.
You will thrive in this role if you:
- Have a strong interest in machine learning, data science, software engineering and energy markets
- Have a solid understanding of data science and machine learning principles, combined with familiarity with software development
- Alternatively, bring strong software development skills with a working knowledge of data science and machine learning concepts
- Are proficient in Python
- Have experience with machine learning libraries such as Scikit-learn, XGBoost, TensorFlow or similar frameworks
- Are curious, rigorous and eager to learn in a fast-paced trading environment
- Enjoy solving complex problems and turning data into practical, actionable insights
- Are proactive and comfortable working both independently and as part of a team
- Are fluent in English; French is a plus
We are committed to meet the energy needs of a growing population and we are committed to the energy transition. The volatility of the energy trading markets requires excellence in risk management and a culture of innovation. We are fully embracing the digital revolution.
Our people flourish in an environment that promotes expertise, entrepreneurship spirit, agility and a purpose-driven culture, generating boundless opportunities to learn, grow and achieve collaborative success.
Reinforcing the competencies of our people is a key pillar of our culture: we train our people to ensure their development and we pledge to encourage safety in all our actions.
We look for passion, ambition and open-mindedness. While we evolve in a demanding industry that requests to be always on the edge, we cultivate a friendly workplace where our people feel good, where team spirit and respect guide our daily routine, where the diversity of our people and their skills create a nourishing experience for all of us.