Computer Scientist as Quantitative Risk Analyst - Data-Driven & ML Techniques (f / m / d)

Responsibilities

• Work in a highly experienced, collaborative, international, fun team that sits at the heart of E.ON’s new energy trading and procurement unit
• Help shape the quantitative risk management function for a fast-growing trading portfolio spanning power, gas, options, complex financial and physical derivatives, and structured customer business
• Take end-to-end ownership of models : from idea and research, through prototype, to robust, cloud-native production implementation
• Develop, maintain, and enhance quantitative risk and pricing models for market, credit, and liquidity risk, including simulation and valuation tools for complex energy portfolios
• Design and run Monte Carlo and scenario simulations (e.g. for P&L, exposure, stress and what-if analyses) to support decision-making on transaction, portfolio, and business level
• Implement models and analytics in Python as part of a modern cloud-native stack (e.g. Azure, containerized services, Snowflake-based data platform), following clean code and DevOps practices (Git, CI / CD, testing)
• Use and further develop data-driven and ML-inspired approaches (e.g. time series models, tree-based models, regularization, feature engineering) where they add value to risk management and pricing
• Closely collaborate with Trading, Market and Credit Risk, Finance and Tech in agile projects to solve real business problems and deliver tangible value
• Translate complex quantitative concepts into clear, actionable messages for senior, non-technical, and executive stakeholders and continuously explore new methods and research in risk modelling, quantitative finance and data science – and bring the most useful ideas into our production landscape
• Mentor juniors, working students and interns, helping them grow their quantitative, coding and business skills

What you bring

To keep you motivated and healthy we are offering you the following benefits

Inklusion

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