Data Scientist - Power Trading

Summary

Join our team as a Data Scientist – Power Trading and contribute to the green revolution of the electricity market. As part of the Finance team, you will develop and optimize power sourcing, hedging, and trading processes. Key responsibilities include building and maintaining forecasting models for energy consumption and prices, managing the model lifecycle, and supporting data-driven decision-making. You will collaborate with colleagues to ensure data-driven, adaptive energy sourcing strategies. The role requires a Master’s degree in a quantitative discipline, 2+ years of industry experience in forecasting, and strong skills in applied mathematics, machine learning, and software engineering. The company offers a dynamic, open work environment with flexible work arrangements and opportunities for professional development.

Requirements

• Master’s degree in a highly quantitative discipline and 2+ years of industry experience in forecasting
• Strong foundation in applied mathematics, including statistics, stochastic processes, linear algebra, (numerical) analysis, and optimization
• Proficiency in machine learning, forecasting, and time series analysis
• Solid understanding of MLOps and data engineering, including experience deploying ML models to production
• Strong software engineering skills and the ability to write production-level Python code with automated testing
• Basic understanding of trading and risk management—or a willingness to acquire this knowledge to evaluate the business impact of your models
• Hands-on mentality and a self-driven, solution-oriented approach to complex problems
• Excellent communication skills in English (B2–C1), both written and spoken
• Strong team player who thrives in a young, dynamic environment

Responsibilities

• Building and maintaining forecasting models for energy consumption, energy prices, and related variables
• Managing the entire model lifecycle – from development and deployment on AWS to monitoring and regular retraining
• Supporting data-driven decision-making in trading and procurement through robust and scalable models
• You will work closely with colleagues across the business to ensure that our energy sourcing strategies remain data-driven, adaptive, and aligned with market dynamics
• Develop scalable forecasting models for household electricity consumption, PV generation, and EV charging flexibility, capable of handling a large number of households
• Develop forecasting models (e.g., electricity prices) to support risk management and algorithmic trading
• Support the procurement and integration of feature data for models, such as weather forecasts
• Take full ownership of the entire model lifecycle, including deployment on AWS, performance monitoring, and retraining
• Contribute to the development of our hedging and algorithmic trading platform

Preferred Qualifications

• A PhD or similar experience demonstrating your ability to independently solve complex problems that have no off-the-shelf solutions
• Experience working with asynchronously generated sensor data
• German communication skills
• Familiarity with the German energy market
• Previous experience working in start-up environments

Benefits

• Whether you prefer the office, your home desk, or a sunny spot in Sardinia — you work where you work best
• We grow together with personal development paths, learning budgets, and regular knowledge-sharing sessions