Bio

Global data science lead at NASDAQ listed company Cimpress and part-time machine learning researcher. Strategic thinker and technology evangelist. Doing interesting things in a boring but thorough way. Worked hard and played hard at top tier management consultancy and big four audit firm.

Professional experience

Currently, I'm a Data Science Manager within the NASDAQ listed company Cimpress responsible globally for our site product recommendation models. Prior to that, I ran data mining techniques to identify patterns in customer behaviour. Furthermore, I applied machine learning on unstructured text data to extract strong segmentation signals. The creation of dashboards and running statistical tests to measure and track the performance of marketing activities were also part of my work. Moreover, I coach and train more junior colleagues. My toolset includes collaborative filtering, statistical data analysis (both Bayesian and frequentist), unsupervised pattern recognition and supervised classification methods, and scalable data processing pipelines in Apache Spark.

I worked on high-level strategy projects during my time at The Boston Consulting Group as a specialist in the area of data analytics. I performed data analyses and built predictive models for a variety of data sets ranging from pricing, procurement, customer intelligence, or portfolio optimization. Furthermore, I developed analytical tools and prototypes of management information systems. Moreover, I coached and trained junior colleagues.

During my time at the big four audit company PricewaterhouseCoopers, I performed IT and process audits and subsequently advised my clients how to improve their processes and IT systems. Furthermore I performed forensic data analyses in order to identify fraud.

In 2008, I did an internship at cominvest Asset Management in the area of investment fund sales reporting. cominvest was eventually merged by absorption with Allianz Global Investors.

During my time at the University of Muenster, I worked as a student assistant at the Marketing Center Muenster primarily responsible for survey design and implementation, and data pre-processing for several analyses like cluster or conjoint analysis.

Last but not least, I worked eight years as a freelancer developing mostly web based applications (LAMP stack) for clients like ESCP University, LexisNexis Germany etc.

Education

I have a MSc with distinction in Information Systems from the De Montfort University Leicester, UK with a specialization on machine learning.

Prior to that, I achieved a BSc in Information Systems from the University of Muenster, Germany with a focus on business process optimization and knowledge management.

A also spent two terms abroad at the University of Seville as part of the Erasmus programme.

Teaching and talks

Problem Solving - Vistaprint Analytics (October 2017)
Training about the hypothesis-driven problem solving approach for all new hires as part of the core training curriculum.

Deep Learning for Image Classification - De Montfort University Leicester (Summer term 2017)
Guest lecture in the area of deep learning for computer vision in the postgraduate module IMAT5234 Applied Computational Intelligence.

Deep Learning for NLP and Text Mining - De Montfort University Leicester (Summer term 2016)
Guest lecture about my research in the area of deep learning in the postgraduate module IMAT5234 Applied Computational Intelligence.

Taming Text with the Elephant - Vistaprint Analytics (December 2015)
A tech talk about the fundamentals of natural language processing and text mining, and how it can be applied at scale with Hadoop.

Pac Man, Neural Networks, and Artificial Intelligence - Vistaprint Analytics (May 2015)
A tech talk showing up current trends on the use of artificial neural networks in computer games and possible business use-cases.

Skills

Machine learning

Linear models, decision trees, random forests, k-nearest neighbors, artificial neural networks, k-means clustering, hierarchical clustering, self-organizing maps, bagging, boosting, scikit-learn, PyTorch, TensorFlow, CNTK, Keras

Programming

Python, Apache Spark, Java, Matlab, Delphi, PHP, VBA

Data analysis

Descriptive and inferential statistics, hypothesis testing, principal component analysis, bootstrapping, SAS, R, SPSS

Data management

SQL (DDL, DML), relational data modeling, dimensional data modeling, MySQL, MS SQL Server, Redshift

Analytics tools

Tableau Software, MicroStrategy, Tibco Spotfire, Looker

Other

HTML, JavaScript, CSS, LaTeX, SVN, Amazon AWS, Microsoft Azure