Andreas Bollig, Developer in Hilden, North Rhine-Westphalia, Germany
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Andreas Bollig

Verified Expert  in Engineering

Artificial Intelligence (AI) Developer

Hilden, North Rhine-Westphalia, Germany
Toptal 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.


Spark, Docker, XGBoost, Scikit-learn, Pandas, Python
Scikit-learn, Pandas, Apache Kafka, Spark, Python
RWTH Aachen University
LaTeX, Python, MATLAB




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.

Work Experience

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.


Python, C


Pandas, Scikit-learn, XGBoost


Data Science


Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT)


Spark, Hadoop




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

2011 - 2016

Doctor of Philosophy (Ph.D.) in Wireless Communications

RWTH Aachen University - Aachen, Germany

2005 - 2011

Master of Science Degree in Computer Engineering

RWTH Aachen University - Aachen, Germany


Cambridge C2 Proficiency

Cambridge Assessment English - University of Cambridge