Munich, Bavaria, Germany
Welcome to my profile! 🙌🏻 🎯 I am a data scientist @ Quantum Black/McKinsey with a strong academic foundation from LMU, TUM, Harvard, and the National University of Singapore (NUS). I am passionate about solving real-world problems through empirical analysis, specifically machine learning and applied statistical modeling. 💼 I have worked on diverse projects ranging from clinical AI applications in breast cancer research (FathomX, Singapore) to ML prototyping in the telecommunication sector (Sopra Steria) and AI consulting as well as product development at appliedAI. My background also includes academic research, marketing analytics, and internships in public policy, equipping me with a broad but data-driven problem-solving mindset. 🎓 I graduated with honors from my two Master’s degrees in Statistics & Data Science (LMU) and Management & Technology (TUM), following my Bachelor's studies in Economics and Political Science which I graduated from with honors. 🔍 I am especially interested in AI for good, meaning some measure social impact, e.g. in reducing or measuring CO2 emissions, boosting preventative healthcare diagnostics, or improving public sector innovation. But honestly, I can wrap my head around any cool idea, I just love it when there is good data available to have fun with! ;) • Tools & Languages: Python, R, Java, SQL, Tableau, STATA, MS-Office • Based in Munich and open to on-site, hybrid (prefered), or remote work
Conducting research on causal inference and economic history as a GSAS Visiting Fellow.
FathomX is a spin-off from the National University of Singapore (NUS). The startup focuses on the development of AI solutions for breast cancer diagnostics and preventative care. In my role on the Research & Science team, I worked on validating and developing novel features for the existing AI solution. More precisely my responsibilities included: • Conducting research on issues related to breast cancer including screening of papers, preparation of clinical studies, and programming new approaches (POC-phase) • Wrote one academic paper on breast density classification with AI focussing on subgroup fairness during inference
TUM.ai is Europe's biggest student initiative revolving around Artificial Intelligence (AI). As a member of Partners & Sponsors department, my focus is on external collaborations and partner management.