CV

Contact Information

Name Simon David Lindner
Professional Title Data Scientist & Complex Systems Researcher
Email lindner.sd@gmail.com
Location Vienna, Austria

Professional Summary

Data scientist and complex systems researcher applying network science and machine learning to healthcare, epidemiology, and natural language processing.

Experience

  • 2026 - present

    Austria (Remote)

    Research Associate
    SUSTech-ETH Institute of Risk Analysis, Prediction & Management (Risks-X)
    • Analyzing longitudinal legal data to construct dynamic language networks, tracking semantic shifts and structural evolution over time.
  • 2024 - 2025

    Vienna, Austria

    Data Scientist
    Leto Space GmbH
    • Designed and evaluated machine-learning models for information extraction from unstructured data.
  • 2020 - 2024

    Vienna, Austria

    Researcher (Complex Systems & Computational Health)
    Complexity Science Hub Vienna / Medical University of Vienna
    • Member, Austria’s COVID-19 Forecasting Committee: developed wastewater-based and short-term epidemic forecasts that informed national public health decisions.
    • Analyzed electronic health records to map multimorbidity networks, uncovering gender-specific associations and socioeconomic health disparities.
    • Built privacy-preserving analytics for international collaborations using synthetic data generation and federated learning.

Education

  • 2020 - 2026

    Vienna, Austria

    PhD
    Medical University of Vienna
    Complex Systems
    • Dissertation: Data-driven approaches to healthcare analytics, multimorbidity networks, and wastewater-based epidemiology.
  • 2017 - 2020

    Vienna, Austria

    MSc
    University of Vienna
    Physics
    • Thesis: Thermodynamics of systems with emergent structures.
  • 2012 - 2017

    Vienna, Austria

    BSc
    University of Vienna
    Physics
    • Thesis: Methods for van der Waals Corrections in Ab Initio Molecular Dynamics.
  • 2010 - 2012

    Zürich, Switzerland

    ETH Zürich
    Undergraduate Studies

Skills

Python: NumPy, Pandas, scikit-learn, TensorFlow, PyTorch, Statsmodels
Data Engineering: SQL, ETL pipelines, large-scale data processing
Tools: Git, Docker, Linux, LaTeX, R, MATLAB
Visualization: Matplotlib, Plotly, interactive dashboards
Statistical Modeling: Regression (LASSO, Ridge, GLMMs), Survival Analysis, Bayesian inference
Machine Learning: Random Forests, Gradient Boosting, SVM, dimensionality reduction (PCA, UMAP)
Deep Learning (Expert): CNNs, RNNs/LSTMs, transfer learning
NLP & LLMs: BERT, GPT, transformer fine-tuning, prompt engineering
Network Science: Graph analysis, agent-based modeling, epidemic models (SIR/SEIR)

Languages

German : Native speaker
English : Fluent