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Data Scientist
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Standort: Berlin, BE, DE Home Office, DE Wildpoldsried, BY, DE- Stellen-ID: 3794**At the earliest date possible we are looking for support for our #teamsonnen**:
Clean and affordable energy for all is one of the greatest challenges of our time. Sonnen has been committed to this mission since 2010 and is now represented in Europe, the USA and Australia with over 1,000 team members globally. In Germany, our offices are located in the beautiful Wildpoldsried (Allgäu) and the vibrating heart of Berlin Kreuzberg.
At sonnen, we are building the energy system of the future. To this end, we are developing new technologies and business models that have not existed before. Whether intelligent power storage, virtual power plants or digital services - we set the trends of a new energy world. That means, among other things, the inexpensive production and storage of renewable energy and the intelligent networking of producers and consumers. sonnen thereby gives people around the world the opportunity to become independent of fossil fuels and conventional energy supplier.
We are growing steadily and are looking for people who want to join us in our vision of clean and affordable energy for all while making a positive impact on climate change.
**About the Role**
We are seeking an experienced Data Scientist to join a cross-functional team of data scientists, data engineers, and business analysts. Our team leverages various data resources at sonnen to develop data-driven insights and services that improve the quality of our product offerings and the performance of our global fleet of energy storage systems.
As a member of the Data Science team, you will develop tools to monitor the performance of our batteries, to identify potential problematic systems, and to improve the quality of sonnen’s product offerings. In addition, you will collaborate with several of sonnen’s functional units to drive innovation, to develop new business-relevant data products, and to serve our customers with data-driven solutions. You will have a key hand in developing models for time series prediction using data from our worldwide fleet of energy storage systems, and you will help to drive the productization of our data analytics pipelines. You have a curious mind with a strong understanding of data science and software engineering concepts, and you excel in finding clarity on ambiguous business problems.
This is a permanent, full-time position - preferably in Berlin or Wildpoldsried. We’re looking for someone who shares our values, who isn’t afraid to challenge existing processes, and who would like to work on innovative solutions in a fast-moving environment. If this sounds like you, then we look forward to hearing from you.
**Your responsibilities**
- Gather and analyze data to optimize and improve existing products, to guide business strategies, and to discover potential new digital solutions.
- Build state-of-the-art prescriptive and predictive algorithms for sonnen’s global fleet of energy storage systems by leveraging new and existing data sources.
- Develop and implement tools that enable sonnen’s operational units to improve the quality and speed of their processes, improve customer satisfaction, and mitigate risk.
- Develop automated approaches to predictive maintenance by leveraging artificial intelligence / machine learning (AI/ML).
- Build key components of ETL and analytics pipelines, and deploy them into an operational analytics environment.
- Guide our data engineering team on data quality and data governance issues.
- Proactively perform analyses and develop proofs-of-concept to unlock insights that can be further developed into customer products and service offerings.
- Collaborate with data engineers, other technology teams, and with business analysts from functional teams across all project phases from ideation to design, development, and product deployment.
**Your qualification**s**
- 2+ years of working experience in data science / machine learning, with a track record developing data-driven analytical services and products.
- Master’s degree or PhD in Data Science, Computer Science, Power Systems Engineering, Physics, or another quantitative field.
- In-depth knowledge of data science and machine learning, with a strong foundation in statistics.
- Experience working with time series data.
- Experience with the full analytics lifecycle including gathering data, analysis, testing, implementation, and communication of results.
- Proficiency with python, SQL, and standard data science libraries (scikit-learn, pandas, torch/tensorflow).
- Ability to gather and manipulate data, to draw insights from large data sets, and to put code into production.
- Knowledge of power systems, energy grids, or energy storage systems is a plus.
- Experience with cloud-computing and Big Data environments (AWS, Databricks, Spark) is a plus.
- A founders mentality: ability to conceptualize and solve data problems and to quickly
