Aktiviere Job-Benachrichtigungen per E-Mail!

(Senior) Data Scientist (m/f/d) - Energy Tech Start Up

Green Fusion GmbH

Deutschland

Hybrid

EUR 60.000 - 90.000

Vollzeit

Vor 30+ Tagen

Zusammenfassung

A leading company in energy optimization, Green Fusion GmbH is seeking a (Senior) Data Scientist to enhance their Energy Optimization Team. This role involves developing algorithms, cleaning and analyzing data, and working collaboratively to promote energy efficiency and reduce emissions to combat climate change. Join a motivated and dynamic team in the heart of Berlin, and make a real impact on the energy transition.

Leistungen

Flexible working hours
Home office and remote work options
Ongoing training opportunities
Employee benefits like Urban Sports Club
Regular team events

Qualifikationen

  • Strong skills in statistics, data modeling, and machine learning.
  • Experience with data analysis and predictive modeling.
  • Familiar with full product lifecycles and collaborative coding practices.

Aufgaben

  • Clean and analyze data to identify patterns and drive solutions.
  • Build data models to predict heating system behavior.
  • Develop production-ready algorithms and collaborate with teams.

Kenntnisse

Data Analysis
Statistics
Machine Learning
Data Modeling
Collaboration

Ausbildung

Degree in Computer Science
Degree in Data Science
Degree in Electrical Engineering
Degree in Mechanical Engineering
Degree in Physics
Degree in Mathematics

Tools

Python
SQL
GraphQL
REST
Pandas
SciPy
Scikit-Learn
Git
Jobbeschreibung
Digitalization and energy transition in one sentence?
That's what we do at Green Fusion!

Our software optimizes heating systems in the real estate sector, helping to combat climate change through digitalization and automation. We reduce emissions and energy consumption, actively advancing the energy transition.

As a (Senior) Data Scientist, you'll support our Energy Optimization Team by developing production-ready algorithms that optimize heating system operations. With a basic understanding of heating systems and strong expertise in control technology, you'll bring essential insights to help us develop effective tools for energy optimization.

Tasks

  • 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 present your findings in a clear, concise, and understandable way.
  • 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.
Requirements

  • 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 familiar with testing frameworks and quality assurance processes to ensure robust, reliable product features.
  • Your code is clean, well-structured, maintainable, and easy for others to understand and build upon.
  • You are comfortable collaborating and communicating effectively with energy engineers, developers (frontend and backend), and customer success managers.
  • You have a strong understanding of customer needs and know how to translate them into technical solutions.
  • You are fluent in English and have a basic command of German.
  • You are living in Berlin.
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.

Direct impact through your job - with us, you can actively contribute to the energy transition and fight against climate change every day.

We value our team - that's why regular team events are very important to us.

The best team that Berlin has to offer - and maybe even beyond. Don't believe it? Then find out for yourself and apply now!

While we are still considered pioneers today, we can soon dominate the market with you! First in the DACH region, then throughout Europe.

You can expect a motivated, open-minded, and dynamic environment that is passionate and ambitious about actively shaping the energy transition - a goal that can only be achieved together!

We look forward to your application - Fernanda will get in touch with you!
Hol dir deinen kostenlosen, vertraulichen Lebenslauf-Check.
eine PDF-, DOC-, DOCX-, ODT- oder PAGES-Datei bis zu 5 MB per Drag & Drop ablegen.