Quantitative / Machine Learning Engineer in Genève

h3Context Environment /h3 pTotalEnergies is developing its activities across the power value chain, with a growing portfolio of renewable generation, flexible assets and power supply activities across Europe. /p pWithin Trading Shipping, our algorithmic trading teams are building advanced quantitative and machine-learning solutions to support trading and optimization activities in European short-term power markets. /p pAs a bQuantitative / Machine Learning Engineer /b, you will join a highly technical and collaborative environment at the intersection of benergy trading, quantitative modelling, machine learning and software engineering /b. /p pYou will contribute directly to the development of models and algorithms used to identify and capture opportunities in European power markets, working closely with quantitative analysts, algorithmic traders, data scientists and IT specialists. /p pThe role offers significant exposure to fast-moving energy markets and the opportunity to work on models that move from research and back-testing through to live production and ultimately contribute to trading performance. /p h3Activities /h3 pYou have a strong quantitative background and enjoy applying advanced modelling techniques to complex, real-world problems. /p pWe are looking for someone with: /p ul liAn engineering degree, Master's degree or PhD in a quantitative field such as bMathematics, Physics, Machine Learning, Computer Science or a related discipline /b. /li liApproximately b2–3 years of professional experience working with machine-learning models in production /b, ideally involving live forecasting or other real-time applications. /li liStrong proficiency in bPython /b. /li liExperience with bMongoDB, SQL and Shell scripting /b. /li liA solid understanding of software architecture and production-quality development practices. /li liExperience with bDocker /b and familiarity with DevOps/MLOps environments, including bCI/CD pipelines /b. /li liStrong knowledge of machine-learning techniques, including supervised and unsupervised learning. /li liPractical experience with btime-series modelling and analysis /b. /li liThe ability to analyse complex systems and identify direct and indirect relationships between multiple signals and datasets. /li liStrong communication skills and the ability to explain quantitative results clearly to both technical and business stakeholders. /li liThe ability to work effectively in a fast-paced, collaborative trading environment. /li /ul h3Additional Assets /h3 pThe following would be considered an advantage: /p ul liPrevious exposure to benergy, commodities or financial markets /b. /li liUnderstanding of European power markets, power generation or energy supply mechanisms. /li liExperience working with trading signals, forecasting models or optimization problems. /li liFamiliarity with project-management and collaborative tools such as bJira, Asana or Monday.com /b. /li /ul h3Why Join Us? /h3 pThis role offers the opportunity to work at the forefront of bdata science and algorithmic trading within the energy sector /b. /p pYou will work on advanced quantitative models with a direct connection to live markets and trading decisions, while collaborating with experienced professionals across trading, quantitative research and technology. /p pYou will join an international environment where machine learning and quantitative analysis play an increasingly important role in optimizing TotalEnergies' activities across European power markets. /p h3Candidate Profile /h3 pAs part of the Algorithmic Trading team, you will: /p ul liDevelop quantitative and machine-learning models supporting algorithmic trading strategies in European power markets. /li liBuild models across the full lifecycle, from data preparation and feature engineering through model training, optimization, validation and live deployment. /li liDesign new indicators, signals and features to improve quantitative and machine-learning trading models. /li liAnalyse large and complex datasets to identify patterns, relationships and trading signals. /li liConduct quantitative research on European power markets and translate market observations into actionable modelling ideas. /li liMonitor the performance and robustness of models in both simulated and live trading environments. /li liContinuously assess model behaviour and identify opportunities to improve forecasting accuracy and trading performance. /liliContribute to rigorous back-testing, validation and model-performance methodologies. /li liWork with cross-functional teams to bring models into production and ensure their reliability, scalability and maintainability. /li liCollaborate closely with algorithmic traders and technology teams to turn quantitative research into operational trading solutions. /li liContribute your data science expertise to broader modelling and optimization topics within the team. /li /ul pJoining TotalEnergies means committing to the energy transition and helping provide energy that is more affordable, more available, and more sustainable for as many people as possible. You will grow within an international multi-energy company where every talent matters. You will contribute to ambitious projects and deliver concrete solutions to today's energy challenges. /p pThroughout your career, you will benefit from a wide variety of assignments and tailored learning opportunities. You will fully develop your potential in an environment that fosters innovation and excellence. Join committed and collaborative teams where success is built together. /p pWe place respect and employee well-being at the heart of our performance. That is why TotalEnergies values diversity and promotes equal opportunities for all. /p #J-18808-Ljbffr