Helping decision-makers avoid costly decisions driven by overconfident models

I work at the intersection of quantitative risk and decision-making, helping decision-makers identify model risk and hidden assumptions before they lead to costly decisions.

• C++1 J.
• Handelsgesetzbuch1 J.
• International Accounting Standards
• Microsoft Excel1 J.
• Python
• SAS-Programmierer1 J.
• SQL1 J.
• VBA (Visual Basic for Applications)

I work as an Actuarial Analyst in regulated financial environments, contributing to quantitative analyses and actuarial reporting where risk awareness, numerical consistency and transparency are essential.

My work focuses on making risk and uncertainty visible through structured quantitative analysis, clear assumptions and reproducible calculation logic. I place strong emphasis on results that are internally consistent, traceable and suitable for review, supporting sound decision-making under regulatory and audit requirements.

A central part of my work is data-driven analysis and automation. I work with structured and unstructured datasets, develop analytical workflows and automate recurring calculations using VBA, Python, C++, SQL and SAS. This helps reduce manual effort, improve robustness and ensure that analytical outputs remain reliable and reproducible over time.

Beyond classical actuarial calculations, I apply data science principles such as exploratory data analysis, feature-based reasoning and systematic model comparison to better understand drivers, sensitivities and uncertainties in quantitative results. Where appropriate, I use statistical and machine-learning-oriented methods to support pattern recognition, segmentation and scenario analysis in an interpretable and controlled manner.

In actuarial consulting, I support analyses performed under HGB and IFRS-related frameworks, working with assumptions, sensitivities and scenario logic. My approach emphasizes risk-sensitive interpretation of results and clear communication with reviewers, auditors and senior stakeholders.

Previously, at ERGO Group AG, I worked on data-driven actuarial analyses, model comparisons and target–actual evaluations, contributing to more stable forecasts and consistent reporting outputs across different internal functions.

My academic background in Physics (M.Sc.) underpins my way of working: analytical rigor, statistical thinking and a disciplined approach to uncertainty. I am comfortable operating at the intersection of actuarial analysis, risk management and data-driven modeling.

I continue to develop professionally through further qualifications (DAV, CFA Level I) while deepening my expertise in quantitative methods, data science and machine-learning-informed analysis within regulated financial contexts.

Focus areas:

Actuarial & quantitative analysis · Risk-aware modeling · Data-driven analytics & automation · Interpretable ML approaches · Audit-ready reporting

Looking for:
Actuarial, risk and quantitative roles in regulated environments