Weather ML & Quant Research Internship in Energy Markets

Engelhart; Grenoble; Sur place; EUR 15 000 - 20 000; Plein temps

Résumé du poste

Engelhart in Grenoble offers a six-month Weather Quantitative Research Internship focused on applied weather research and its impact on energy markets. You’ll work with a team of experts to study weather phenomena, leverage Python for data analysis, and develop forecasting techniques.

The role provides mentorship from experienced professionals and exposure to meteorological datasets and AI-based forecasting methods within a trading-focused environment.

Qualifications

• Enrolled in a master’s degree internship or equivalent in a quantitative field such as Meteorology, Atmospheric Sciences, CS or ML.
• Strong Python skills for data analysis, manipulation and modelling.
• Solid background in machine learning, statistics or quantitative modelling methods.
• Evidence of completing a substantial research or data science project.
• Interest in weather forecasting and its application to energy markets.
• Business-level English proficiency and ability to work in France for the full duration.

Responsabilités

• Study a weather phenomenon and understand its physical and statistical features.
• Assess its relationship with energy-market outcomes for trading decisions.
• Source, clean and analyse meteorological and market data using Python.
• Develop, test and evaluate forecasting approaches to improve accuracy.
• Compare model outputs and document assumptions and limitations.
• Present methods, findings and recommendations to stakeholders.

Connaissances

Python

Machine Learning

Data analysis

Statistical modelling

Mathematical modelling

Weather forecasting interest

English communication

Formation

Master’s degree in Meteorology/Atmospheric Sciences/CS/ML

Outils

NumPy

Pandas

Jupyter

Description du poste

Engelhart in Grenoble offers a six-month Weather Quantitative Research Internship focused on applied weather research and its impact on energy markets. You’ll work with a team of experts to study weather phenomena, leverage Python for data analysis, and develop forecasting techniques.

The role provides mentorship from experienced professionals and exposure to meteorological datasets and AI-based forecasting methods within a trading-focused environment.