Senior Data Scientist (m/f/d)

E.ON Drive Infrastructure

2d•Hybrid

About The Position

As a Senior Data Scientist in E.ON Drive Infrastructure’s newly established AI UNIT, a special unit built and run like a startup, you will help transform complex business challenges into data-driven decisions for a pan-European business. Working with stakeholders across the organization, you will develop analyses, experiments, and models that create measurable business impact and support AI-driven decision-making. This is a senior individual contributor role that also includes sharing knowledge and supporting junior colleagues. The position reports to the Head of AI Strategy.

Requirements

Proven experience delivering analyses and models that influenced real business decisions.
Strong background in statistics, including hypothesis testing, experimentation, and causal inference.
Excellent programming skills in Python and SQL.
Deep expertise in at least one area such as forecasting, optimization, causal inference, or Bayesian methods.
Ability to communicate complex analytical findings to non-technical audiences.
Strong commercial mindset focused on business impact and value creation.
Experience working with machine learning techniques and data-driven decision-making frameworks.
Curiosity, pragmatism, and passion for solving complex problems through data and AI-driven insights.

Nice To Haves

Experience taking models into production.
Hands-on experience with GenAI or LLM-based tools.
Experience in energy, mobility, or other asset-heavy industries.

Responsibilities

Translate business challenges into analyses, predictive models, and actionable recommendations.
Build and validate statistical, machine learning, and optimization models to support strategic decision-making.
Design experiments and measure real business impact using rigorous analytical methodologies.
Collaborate with AI/ML Engineers to bring analytical models into production environments.
Communicate insights, assumptions, and uncertainty clearly to stakeholders, including at CEO level.
Establish best practices and standards for analytics, experimentation, and model development.
Evaluate emerging AI models, AI tooling, and agentic systems, and use effective tools to accelerate analysis workflows.
Drive data-informed decision-making across business functions and regions.
Share knowledge and support the development of junior colleagues.