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 November 22, 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




Hilden, North Rhine-Westphalia, Germany



Preferred Environment

Databricks, Spark, Scikit-learn, Docker, Python

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: Spark, Docker, XGBoost, Scikit-learn, Pandas, Python
  • 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: Scikit-learn, Pandas, Apache Kafka, Spark, Python
  • 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: LaTeX, Python, MATLAB


  • Inventory Forecast

    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

    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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