1KOMMA5°

We are looking for you as an addition to our tech-team in Berlin, Munich or Hamburg. 1KOMMA5° is building Germany's largest one-stop-shop for sale, installation and services related to solar, heat pumps, electricity and charging infrastructure. And they are all connected! Be a part of our mission!

Become a part of our mission and learn about our Product & Tech team!

Deine Position

As a Data Scientist, you will be a core member of our cross-functional team, responsible for designing and implementing advanced data-driven solutions to accelerate the energy transition. Your work will focus on complex time series data, building robust data pipelines, and leveraging your expertise in a dynamic environment. You'll directly impact our products and services, helping to shape the future of the energy sector.

Key responsibilities include but are not limited to:

• Develop, improve, and deploy advanced machine learning models mainly for forecasting timeseries data but not limited to
• Collaborate on designing and implementing scalable data science solutions on cloud infrastructure (Google Cloud Platform) to ensure high performance, reliability, and security
• Design, develop, and maintain robust data pipelines for ingesting, transforming, and processing large-scale time series data
• Apply advanced analytical techniques to extract actionable insights from complex datasets, supporting strategic decisions for product development and business growth
• Collaborate with engineers and product managers to translate business needs into technical requirements and deliver end-to-end data products
• Promote best practices in data science, including code quality, testing, and documentation Technologies you will work with include:
• Python and SQL
• Data analysis and machine learning libraries (pandas, numpy, scikit-learn)
• Google Cloud Platform (GCP) and Terramate/Terraform
• SQLMesh and Looker
• Numerical optimization and solvers (Pyomo)

Dein Profil

The successful candidate will have:

• You have 3+ years of experience as a data scientist or in a similar role, with a proven track record of delivering end-to-end data projects
• You have deep expertise in Python and SQL, and are proficient with data analysis and machine learning libraries (e.g., pandas, numpy, scikit-learn)
• You have extensive experience with time series data, including feature engineering, model selection, and validation
• You are a master of dynamic environments and thrive on solving complex, real-world problems
• You have hands-on experience with cloud platforms, particularly with services for data processing and machine learning (e.g., Google Cloud Platform)
• You are proficient in building and maintaining production-level ML and data pipelines
• You are an excellent communicator and thrive in a collaborative, agile setting Bonus points for:
• Experience with numerical optimization and solvers (e.g., Pyomo, Gurobi, or similar) is a significant plus
• Knowledge of energy markets and renewable energy systems
• Experience with data visualization tools like Looker We are an ambitious and dynamic company with a talented team. We require our engineers to be imaginative, enthusiastic, and willing to tackle new challenges as we strive to provide everyone with renewable energy technologies.

Benefits

• You are part of a dynamic team with people who prove every day that they can make things happen and move companies forward with great positive impact
• You move in flat hierarchies and have short decision-making paths. You can learn a lot quickly and get involved at different levels
• You will be welcomed by a friendly and familiar team
• You are part of the energy transition and recognize in your daily work what purpose it serves
• You can work in one of our offices in Hamburg, Berlin or Munich
• You create a healthy balance alongside your work and enjoy all the benefits of the EGYM Wellpass
• Benefits and discounts are yours with Futurebens
• Whether city bike or e-bike - be flexible with our job bike leasing and do something good for the environment at the same time

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