Company Description

At T-Systems, you will find groundbreaking projects that contribute to social and ecological well-being. We want to welcome new talents like you, who bring fresh ideas, different points of view, who accept challenges and continuous learning, to grow and impact society... All this, in a fun way!

It doesn't matter when or where you work. It's about doing work that matters to move society forward. For this reason, we will do everything possible to ensure that you have every opportunity to develop by offering you a support network, excellent technology, a new work environment and the freedom to work independently. We support you to constantly grow both personally and professionally, so that you can leave a notable mark on society.

T-Systems is a team of around 28,000 people employed around the world, making us one of the world's leading providers of integrated end-to-end solutions. We develop hybrid cloud and artificial intelligence solutions and drive the digital transformation of companies, industry, the public sector and, ultimately, society as a whole.

Job Description

Data Scientist - Focus Renewable Energy Role

Summary

We are looking for a business-oriented Senior Data Scientist with strong experience in data transformation and visualization, eager to transform complex data into actionable insights. The candidate will mostly work on topics related to (renewable) energy, e.g. PV/Solar generation, BESS management, consumption analyses, and other typical automation/digitization tasks within an energy provider. The role focuses on analytical problem solving, development of models and dashboards, and supporting data-driven decision-making in close collaboration with the business side.

Key Responsibilities

• Conduct exploratory data analyses and derive insights that support decision-making
• Build advanced dashboards and simulation tools based on the requirements by the business side and translate business requirements into suitable technical solutions
• Communicate analytical findings and model results clearly to business and technical stakeholders
• Prepare model-ready datasets in collaboration with data engineers; implement feature engineering using Python and SQL.
• Present insights, model results, and recommendations in a clear and actionable way to non-technical stakeholders, enabling data-driven decision-making.

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