Andreas Bollig, Artificial Intelligence (AI) Developer in Hilden, North Rhine-Westphalia, Germany
Andreas Bollig

Artificial Intelligence (AI) Developer in Hilden, North Rhine-Westphalia, Germany

Member since October 9, 2019
With a Ph.D. in electrical engineering and extensive experience in building machine learning applications, Andreas spans the entire AI value chain, from use case identification and feasibility analysis to implementation of custom-made statistical models and applications. Throughout projects, he stays focused on solving the business problem at hand and creating value from data.
Andreas is now available for hire



  • Python, 8 years
  • Artificial Intelligence (AI), 4 years
  • XGBoost, 4 years
  • Scikit-learn, 4 years
  • Data Science, 4 years
  • Spark, 4 years
  • Docker, 3 years
  • Natural Language Processing (NLP), 3 years


Hilden, North Rhine-Westphalia, Germany



Preferred Environment

Python, Docker, Scikit-learn, Spark, Databricks

The most amazing...

...machine learning solution I have built is a fully automated cloud-based end-to-end cost-type proposer for GL bookings.


  • Senior Data Scientist

    2017 - 2019
    • Built multiple machine learning applications (classification and time series forecasting) including tech stack selection, architecture, model training, and deployment.
    • Mentored junior data scientists in multiple projects incl. own contributions: marketing analytics based on IoT data, production optimization, accounts receivable prediction, epigenetics research, hair color prediction from sensor measurements.
    • Consulted and performed QA in multiple machine learning projects with external implementation partners-contexts: source-to-pay, intercompany, EDI.
    Technologies: Python, Pandas, Scikit-learn, XGBoost, Docker, Spark
  • Data Scientist

    2016 - 2017
    • Helped build the inhouse data lab and established data science approaches at the company.
    • Built statistical models for customer churn prediction.
    • Implemented Spark data preparation and pseudonymization solutions on Hadoop.
    Technologies: Python, Spark, Kafka, Pandas, Scikit-learn
  • Scientific Staff

    2011 - 2016
    RWTH Aachen University
    • Participated in three research projects and contributed to eight applications for research grants, publishing research papers at top international conferences and journals.
    • Analyzed large datasets and performed distributed Monte Carlo simulations.
    • Supervised students writing theses and working as student research assistants.
    Technologies: MATLAB, Python, LaTeX


  • Inventory Forecast (Development)

    To provide the controlling department ample time for preparing devaluation numbers for the month-end closing in the context of slow-moving inventory, I built a machine learning solution that forecasts inventory quantities for a big number of materials and makes the data usable via a web-based dashboard.

  • Cost-type Proposer (Development)

    When bookings in a company's ERP system carry the wrong cost types, the controlling department gets a distorted view of the company's expenses. To this end, I developed a machine learning solution that proposes a cost-type (GL account) for each booking and provides this data to the controlling department via the company's BI system.


  • Languages

    Python, C
  • Libraries/APIs

    Pandas, Scikit-learn, XGBoost
  • Paradigms

    Data Science
  • Other

    Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP)
  • Frameworks

    Spark, Hadoop
  • Tools

  • Platforms

    Linux, Docker, Databricks, Apache Kafka, Xen, TinyOS


  • Doctor of Philosophy (Ph.D.) in Wireless Communications
    2011 - 2016
    RWTH Aachen University - Aachen, Germany
  • Master of Science degree in Computer Engineering
    2005 - 2011
    RWTH Aachen University - Aachen, Germany
  • Cambridge C2 Proficiency
    Cambridge Assessment English - University of Cambridge

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