Our software optimizes heating systems in the real estate sector, helping to combat climate change through digitalization and automation. As a (Senior) Data Scientist, you’ll support our Energy Optimization Team by developing production-ready algorithms that optimize heating system operations. You clean and analyze data to identify patterns and trends, uncovering insights that drive our solutions.
You apply statistical techniques to interpret data, ensuring the reliability and accuracy of your findings.
You build data models to predict heating system behavior and patterns using advanced analytics and machine learning.
You develop production-ready algorithms and data pipelines to optimize energy system components, reduce CO₂ emissions, and enhance energy efficiency.
You're responsible for the full development cycle of product features — from understanding customer requirements to final deployment — collaborating closely with energy engineers, frontend and backend developers, and product and customer success managers.
You analyze experimental data to refine and improve energy optimization algorithms.
You support the team in creating data models for predicting energy time series data (e.g., heat demand, solar production, electricity consumption) and in optimizing energy systems using machine learning techniques, including supervised, unsupervised, and reinforcement learning.
You are familiar with full product lifecycles — from feasibility studies and requirement engineering to production-ready tool development, code reviews, feature deployments, and ongoing maintenance and improvement.
You bring strong skills in statistics, data modeling, data analysis, and machine learning.
You have an educational background in electrical engineering, mechanical engineering, physics, computer science, data science, or mathematics — with a solid foundation in energy technologies.
You have expertise in developing prediction models and working with energy time series data.
You are proficient in Python, SQL, GraphQL, and REST, and you work confidently with data science libraries like Pandas, SciPy, and Scikit-Learn. Experience with Machine Learning Operations (MLOps) is a plus.
You have hands-on experience with version control systems like Git and follow collaborative coding practices.
You are comfortable collaborating and communicating effectively with energy engineers, developers (frontend and backend), and customer success managers.
You are fluent in English and have a basic command of German.
Benefits
&##Flexible working hour models, home office, and remote work.
&##Ongoing training opportunities – whether through job challenges, our open feedback culture, or sponsored training programs, there are always opportunities to learn and grow.
&##Employee benefits such as Urban Sports Club or Become1.
&##We value our team – that's why regular team events are very important to us.
&##Don’t believe it?