Quantitative Research Intern

📍Location: Campus ENGIE - La Garenne -Colombes

About ENGIE and Supply & Energy Management:

ENGIE, a global leader in low-carbon energy and services, relies on its Global Business Unit Supply & Energy Management (GBU S&EM) to provide reliable, sustainable, and affordable energy to all its customers. This strategic unit optimizes the Group’s and clients’ production assets and designs tailored energy solutions for our 200,000 professional clients and 15 million consumers.

The Global Business Unit Supply & Energy Management leverages ENGIE’s assets to deliver secure and sustainable energy to its B2B and B2C customers. It uses its expertise in energy management to provide decarbonized electricity 24/7.

Joining Supply & Energy Management means becoming part of a team of over 10,000 passionate experts spread across 20 countries, all united by a shared mission: shaping a greener and more efficient energy future. Together, we push the boundaries of innovation to deliver decarbonized energy 24/7. Join us and be part of those shaping the energy of tomorrow!

Context

As part of the Gas & Electricity Market-Making Team, you will contribute to quantitative research focused on weather and its impact on short-term power markets. Working closely with traders, you will help improve the understanding of market dynamics and the influence of weather conditions on energy trading activities.

Your Mission

• Conduct statistical analyses of weather forecast runs to assess their representativeness and accuracy.
• Develop machine learning models to generate synthetic weather scenarios and improve forecast representativeness.
• Align weather forecast runs from different sources and combine them into aggregated datasets that better isolate the weather signal.
• Collaborate with traders to understand market dynamics and translate research findings into valuable market insights.

What we are looking for

Hard skills

• Strong analytical and logical skills.
• Solid foundations in machine learning, probability, and statistics.
• Proficiency in Python.

Soft skills

• Ability to present technical findings clearly.
• Attention to detail.
• Rigorous and methodical approach to research.

Education & Experience

• Master's degree (or equivalent) in a quantitative field such as Mathematics, Statistics, Data Science, Machine Learning, Engineering, Physics, or a related discipline.
• Previous academic or project experience in quantitative research, statistics, or machine learning is a plus.

Languages

• Fluent English.

Why join us?

• Work on real-world challenges at the intersection of weather analytics, quantitative research, and energy markets.
• Collaborate directly with experienced traders and quantitative experts.
• Gain hands-on experience applying advanced statistical and machine learning techniques within a leading energy company.
• Contribute to the energy transition through innovative market research.

Diversity & Inclusion

If you meet these requirements, then you are the talent we are looking for. Don’t wait – apply now with your CV.

At ENGIE S&EM, we are committed to fostering a gender-neutral and inclusive environment where everyone’s potential can thrive.

All our positions are open to people with disabilities. If you need any reasonable accommodations during the recruitment process, please inform your recruiter — we will be happy to support you.

About ENGIE

ENGIE is a global leader in low-carbon energy and services, committed to accelerating the transition towards a carbon-neutral world. Our purpose (“raison d’être”) is clear: act to reduce energy consumption and develop cleaner, more sustainable solutions that balance economic performance with a positive impact on people and the planet.

We rely on our core businesses — gas, power, renewable energy, and services — to deliver competitive, tailored solutions to our customers worldwide.

With 96,000 employees and a strong network of partners and stakeholders, ENGIE is more than a company: we are a community of Imaginative Builders, working every day to create harmonious, sustainable progress.