For Dutch: Over Paul van der Laken

Hi there, welcome to my blog!

I’m Paul, and I like to mess with data.


I’ve always been fond of puzzles and computers. Over time, this developed into a passion for programming and statistics. I particularly enjoy developing systems that leverage automate or optimize decision-making processes. Thereby preventing the human biases observed by Ariely, Kahneman, Tetlock, and their colleagues. Or allowing businesses to operate just a bit more efficient and effective!

For the past decade, I have working in the field of data science and analytics at both multinationals and startups. My career started out in the domain of Human Resources where I actually wrote a PhD dissertation on the topic of People Analytics. I strongly believe quasi-experimentation and data science can help organizations improve their strategic policies. For instance, those policies related to the attraction, development, motivation, and retention of people.

During the past few years, I have been developing machine learning models and expert decision systems to optimize business processes. My models have been used to predict claims fraud, set prices dynamically, extract text and data from documents, estimate customer value and churn likelihood, optimize call center workload and capacity, and many other relevant outcomes. If you want to find out how I can help your business move forward, get in touch!

Next to this, I provide professional education in data-driven management, statistical programming, and data visualization. I give masterclasses and workshops at Erasmus University, TIAS, Tilburg University, and the Jheronimus Academy of Data Science and develop e-learnings for the Academy to Innovate HR. I also develop and facilitate learning programs tailored to organizations, like I did for KPN, Capgemini, IntelligenceGroup, Essent, and many Dutch hospitals and governmental agencies. Do reach out if you’d like to know more!

And I host this data science blog of course! I blog mostly about programming, data visualization, and machine learning. Proper data visualization is essential to communicate the enormous heaps of information generated these days. Particularly interactive ones. Where users can freely explore patterns, unhampered by the intentions and biases of the original creators. Regarding machine learning, I am truly amazed at the ever-increasing pace at which computer algorithms are able to both solve global issues, as well as create ethical challenges along the way.