Data Scientist - Forecasting & Analytics (m/w/d)

Standort: 

Cairo, EG

Stellen-ID:  5329

Join the energy revolution with #teamsonnen!

At sonnen, we’re driven by a clear goal: creating a future powered by clean, affordable energy for everyone. That’s why we make our customers independent – not only from fossil fuels, but also from rising electricity costs.

The key to this independence is our intelligent, all-in-one energy system. It combines solar panels, battery storage, energy tariffs, and wallboxes – all developed and manufactured in Germany.

As the first and only provider in Germany, we also connect thousands of home batteries into one shared network: the sonnenVPP, our industry-leading virtual power plant.

In short: every day, we’re working to shape the energy future. And we’d be thrilled to have you join us!

We are seeking an experienced Data Scientist to join a cross-functional team of Data Scientists and Software Engineers. 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, Forecasting & Algorithms team, you will develop tools to forecast and optimize our customers’ home energy assets, to monitor the performance of those assets and identify potential problematic systems, and to improve the quality of sonnen’s digital product offerings.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 based at the sonnen Tech Center in New Cairo. 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.

 

What you will do to drive the energy transition:

 

  • Build state-of-the-art predictive algorithms for sonnen’s global fleet of energy storage systems by leveraging new and existing data sources.
  • Develop automated approaches to predictive maintenance by leveraging artificial intelligence / machine learning (AI/ML).
  • Gather and analyze data to optimize and improve existing products, to guide business strategies, and to discover potential new digital solutions.
  • Build key components of ETL and analytics pipelines and deploy them into an operational analytics environment.
  • Collaborate with data management and engineering on data quality and data governance issues.
  • 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.

 

What you will need on that journey:

 

  • 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, Mathematics, Physics, or another quantitative field.
  • In-depth knowledge of data science and machine learning, with a strong foundation in statistics, time series analysis, forecasting, and/or optimization models.
  • Proficiency with python, SQL, standard data science libraries (scikit-learn, pandas, torch/tensorflow), and cloud-computing and Big Data environments (AWS, Databricks, Spark).
  • 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.
  • A founder's mentality: ability to conceptualize and solve data problems and to quickly adapt to new challenges or topics. 
  • Written and spoken fluency in English.


Stellensegment: Cloud, Database, Analytics, Computer Science, SQL, Technology, Management