Machine Learning for Wind & Solar Asset Yield Estimation Internship

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Machine Learning for Wind & Solar Asset Yield Estimation Internship

internship · Data Science & Analytics

Context & Environment

Location: Geneva, Switzerland
Proposed internship duration: 6 months
Starting date: ASAP (preferred)

Take your first steps into a fulfilling career and join our team as an intern!

Are you looking to grow your career in the vibrant world of energy trading and shipping?

Are you ready to help us innovate and grow with your entrepreneurial vision?

If yes, we would love to see your profile! 

We are looking for innovative minds ready to take initiative and to help bringing our new projects to life.

Activities

• Develop a machine learning model to estimate the annual energy yield of wind and solar assets, taking into account asset characteristics (e.g., location, technology, turbine type and height, panel configuration, tilt and azimuth) and leveraging TotalEnergies’ proprietary asset and production data.
• Collect, process, and analyze large-scale datasets, including historical weather data (wind speed, solar irradiance, temperature, humidity), asset specifications (technology, capacity, turbine/panel type, tilt, azimuth), and geographical features (elevation, land cover, terrain, and proximity to obstacles).
• Develop, train, and benchmark supervised machine learning models (e.g., Random Forest, Gradient Boosting, Neural Networks) to estimate and predict wind and solar power generation, and assess their performance using appropriate validation and evaluation methodologies.
• Investigate relevant features and modeling approaches to identify the key drivers of renewable energy yield and improve the accuracy, robustness, and generalization of the models across different assets and locations.
• Collaborate with IT and Data Engineering teams to automate data preparation and model execution pipelines, and contribute to the industrialization and deployment of models in a cloud environment.
• Contribute to TotalEnergies’ existing in-house suite of short- and medium-term weather-to-power models, supporting forecasting of wind generation, solar generation, and power demand.
• Develop, maintain, and optimize Python scripts and data-processing workflows to automate recurring analyses, improve operational efficiency, and support the scalability of existing tools.
• Work closely with power, gas, LNG analysts, and traders to understand their business requirements and incorporate their operational and market insights into the development and refinement of the models.

Accountabilities

• Enhance TGP ability to leverage data to model and optimise power assets/portfolios/strategies/risk assessment and help generate additional value for the Company by driving the right trading decisions.
• Reply promptly and reactively to business needs and requests from traders (predominantly power) and management.
• Supply guidelines and support to the teams on any topics involving analysis and modelling of large data sets.

Job dimensions 

• The ‘Modeling & Analysis for Trading Strategies’ department (MATS) aims at providing a better understanding of the markets traded by TotalEnergies Gas and Power (TGP) in terms of power prices and fundamentals, finding ways to model and forecast their dynamics and dealing with complex issues requiring a quantitative approach.
• In a context of great autonomy, the MATS department contributes interpretation, advisory and support to all TGP trading desks and to senior management - including COMEX members - and helps them define trading strategies and take investment decisions. 
• The intern will be part of the ‘Weather Modeling & Analysis’ (WMA) team under the supervision of the manager of the Weather Modeling & Analysis team. 
•  The WMA team brings expertise in weather modelling at different spatial and temporal scales for the different desks since integrating weather information in trading decisions is becoming key (growing share of renewable energies in the electricity generation, climate change already impacting the supply/demand balance, fast development of AI weather models, etc.).
• The WMA team works in close collaboration with other teams, fostering a culture of knowledge sharing and cross-functional expertise. These teams include gas and power market experts, ML/AI experts within TGP.

Candidate Profile

• University educated to at least master’s degree in mathematics, physics or meteorology.
• Strong coding skills in Python with proficiency in common libraries for data science and abilities to deal with large datasets 
• Knowledge of a variety of machine learning techniques and their advantages/drawbacks.
• Ability to write transferrable code that adheres to best practices.
• Knowledge of database technologies (PostgreSQL, MongoDB, S3 bucket).
• Experience with Cloud environments like AWS (S3, EC2, Lambda, etc) will be appreciated. Knowledge in Databricks and Apache Spark programming would be welcome.
• Experience in GitHub for version control, code review, and collaborative data project development
• The internship requires innovation and organisation.
• Capability to explain complex problems and present them in a clear and neat manner.
• Fluent in English – knowledge of French is an advantage.

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.

Additional Information

Domain: Strategy Economics Business

Type of contract: Internship

Experience: Less than 3 years

Employer company: TotalEnergies Gas & Power Ltd