Freelancer profile translated to English.
Back to original languageAbout Nico
Looking for a Data Scientist who can transform complex data into reliable, production-ready models? That's exactly where I come in.
As a physicist (M.Sc., LMU Munich) and Data Scientist with over 2 years of experience at leading research institutions like the Max Planck Institute for Quantum Optics, I develop machine learning and deep learning solutions that perform robustly even with complex, high-dimensional data. My background in physics gives me a deep mathematical and statistical understanding, which I translate into real, impactful models, such as in a project for non-invasive cancer detection with an AUC of around 0.90, published in ACS Central Science.
What I bring:
In-depth expertise in Python (Scikit-Learn, TensorFlow, PyTorch, Pandas), R, and SQL for the entire data science workflow, from data preparation to production-ready models.
Experience in building custom tools and pipelines, such as an internal Python package for automating preprocessing steps, which significantly reduced manual effort for an entire research team.
Peer-reviewed publications in renowned journals (ACS Central Science, Journal of Biophotonics, BMC Medicine), demonstrating that I not only implement projects but also think them through to scientific validation.
Clear, understandable communication of complex results, essential for teams without deep data science expertise.
I can support you with projects in the areas of Machine Learning, Data Analysis, Predictive Modeling, and Deep Learning, whether it involves a single model, a data pipeline, or a deeper analysis. Let's discuss how I can specifically advance your project.
German
Native or bilingual
English
Fluent
Can work on-site
München (up to 50km)
Experience
- Center for Molecular FingerprintingData ScientistRESEARCHJanuary 2026 - Today (7 months)Garching bei München, GermanyDevelopment of customized health monitoring systems based on molecular laser spectroscopy data. My focus is on creating person-specific baselines from longitudinal laser data and early detection of subtle deviations from these baselines to make potential health changes visible even before clinical diagnosis.- Building machine learning pipelines for assigning molecular laser data to individual subjects and for modeling personalized physiological baselines.- Developing anomaly detection methods for early identification of small, clinically relevant deviations from the individual baseline.- Exploring potential biomarkers for early, non-invasive disease detection using molecular and biomedical data.- Close collaboration with an interdisciplinary team of researchers and clinicians, led by Nobel laureate Prof. Ferenc Krausz, to validate the developed models on real patient data.
- Max-Planck-Institut für QuantenoptikData ScientistRESEARCHAugust 2024 - December 2025 (1 year and 4 months)Garching bei München, GermanyDevelopment and optimization of machine learning models for non-invasive lung cancer detection based on clinical laser spectroscopy data (infrared molecular fingerprinting of blood serum). My focus was on the entire pipeline from data preparation to clinical validation, with the goal of reliably linking spectroscopic signals to diagnostically relevant biomarkers.- Development of ML models for cancer detection with an AUC of around 0.90 on clinical laser spectroscopy data, published in ACS Central Science.- Building an internal Python package for automating preprocessing and discretization steps of spectroscopic data, significantly reducing manual effort for the entire research team.- Utilizing deep learning methods to automatically extract meaningful features from infrared spectra of blood serum, reduce noise, and thus better visualize the underlying disease-relevant patterns (published in the Journal of Biophotonics).- Participation in a clinical study evaluating disease progression and survival rates in lung cancer patients using infrared spectroscopy of blood serum, with a focus on prognostic accuracy for personalized treatment planning (published in BMC Medicine).
- IG-Initiativgruppe für Interkulturelle Begegnung und Bildung e.V.TutorEDUCATION AND E-LEARNINGOctober 2020 - September 2025 (4 years and 11 months)Munich, GermanyFreelance individual and group tutoring for around 100 students per year in mathematics, physics, statistics, and programming. In addition to subject matter expertise, my focus was on teaching students and university students a structured, independent understanding of complex quantitative topics.- Individual and group tutoring for around 100 students per year in mathematics, physics, statistics, and programming.- Leading exam preparation courses for German final exams (Abitur, FOS/BOS, Realschule, Mittelschule), focusing on problem-solving strategies and exam tactics.- Supporting bachelor's students in quantitative subjects, especially in clarifying statistical methods and programming concepts for coursework and exams.
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Education
- Master of Science PhysicsLudwig Maximilian University Of Munich2024Master Of Science Physics