Georg Heiler

Georg Heiler

PhD candidate & data scientist

Complexity Science Hub

TU Wien


Vienna Data Science Group


Georg Heiler is a PhD candidate at the Vienna University of Technology and Complexity Science Hub Vienna.

Georg obtained a bachelor’s and a master’s degree in business informatics from the Vienna University of Technology. In his master thesis titled “Cost-based statistical methods for fraud detection", he showed the superiority of an individual cost based machine learning based credit check process over the traditional methodology used at the partner company.

As a data scientist Georg works on E2E analytical pipelines.


  • Geo-spatial analytics
  • Time series
  • Network analytics
  • Large and fast data


  • MSc in Business Informatics, 2018

    TU Wien

  • BSc in Business Informatics, 2015

    TU Wien



H3 conda-forge

Conda forge offers effortless installation of various well tested python packages. I am a maintainer of H3 and H3-py on conda-forge.

Datalake for the enterprise & large geospatial data

Reverse engineering old data pipelines ; ) and analyzing huge quantities of spatial data.

Music streaming Analytics

Anomaly detection for music streaming royalties

Predictive credit scoring

Individual cost based classification model outperforms classical processes.


PredictR is a fintech startup which turns personal transaction lists into cashflow forecasts. It allows customers to explor their financial future to put life decisions into context.


Vienna Data Science Group [VDSG] is a nonprofit association promoting knowledge about data science. I am a member here and help newcomers find their way into data science.

Recent Publications

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  • Josefstädter Str. 39, Vienna, 1080
  • Enter Building 1 and take the stairs to Office 200 on Floor 2
  • Monday 10:00 to 13:00
    Wednesday 09:00 to 10:00
  • Book an appointment