Data Scientist (and self-proclaimed “Pokemon Master”) Vincent D. Warmerdam wants to build systems that solve problems. His motto: “Never let your school get in the way of your education.”
One of the projects for GoDataDriven I’m most proud of is the recommender we built for the website of NPO, the Dutch public broadcast corporation, where visitors can watch television programs. The recommendations were working so much better after we did our thing that my grandfather even congratulated me for it. The rest of the country also noticed; moments after implementation, the recommender broke the caching layer due to a shift in popularity – that was rather cool.
There is a lot of bullshit in consultancy. A herd of elite men in suits making powerpoint presentations about the possibilities of data as the core delivery of their service. At GoDataDriven, we build real stuff, stuff that works and stuff that makes it into production.
Designing Algorithms
My current client is Royal FloraHolland in Aalsmeer, where they auction flowers. Our assignment is somewhat generic: we make them better at what they do by using data. We build systems to predict how much traffic enters the site, fluctuations in the prices of particular flowers, and even to deal with the quality of the flower images. Usually, we take two weeks or so to build a proof of concept, and if it appears useful, we bring it into production in a few months.
I don’t see my job as just designing algorithms- I design and build systems that solve actual problems. When I’m gone, the system must continue to work without me and must be understood by the people who have to work with it. Some data scientists like to brag about how complex their algorithms are. Instead, I get more satisfaction from building a system that is as simple as possible.
Education has always been an important part of my life. I taught myself how to program. I started my career as a freelance developer. In order to grow my network and give something back to the community, I started to give free courses on data science. Now I teach several courses here at GoDataDriven and through Xebia Academy. I also get to work for major clients like ING, NPO and Royal FloraHolland, where there are a lot of cool projects. Gaining access to these companies and working on projects of this scale would be more difficult as a freelancer.
Another cool part of my work here is that GoDataDriven gives its employees a lot of space for personal projects. With a colleague and friends from the community, I was able to co-found PyData. We organize meetups and a yearly conference for developers and users of open source data tools. We thought that there was a lack of technical events where you could actually learn something, and we were very happy that we were able to work together with NUMFOCUS to bring the conference to Amsterdam. I also initiated a partnership with Rstudio. They’ve always impressed me with what they do, so I was very happy to connect with them. I also share some of the lessons I’ve learned on my blog, koaning.io.
A smart and nice way to learn new stuff is to build something with a data engineer in a new language or new technology and then try to present that project at a conference. Last year my colleague Fokko and I worked on a small hobby project that uses Apache Flink, a streaming technology.
We built a model for online video games, to match opponents of the same strength in real time. We showed it to some of the Apache Flink developers, and they were impressed enough that they asked us to submit it to their conference. You can check it here: Flink Forward Berlin – Using ML Algorithms for Online Gaming. Getting asked by the Apache Flink developers to speak at their conference was great, actually being there was a blast.
What I love about my field of work is that when I see that something isn’t okay, I can make an app or tool to solve that problem. The downside of this way of thinking is that it is pretty addictive. At some point, my girlfriend had to tell me that I needed to close the laptop. Now I apply a bit of mental accounting:
I try to figure out if the energy going into an activity is greater than the energy I get out of it. If it is, I should not do it. I’ve seen many people in my field getting hit by burnout and I want to prevent that.
I now know better what gives me energy, and I’m getting better at scheduling my attention. I try to do a bit more sports and take the time to turn off the laptop, so I have more time for my friends, family, and my two felines.
Eager to work alongside Vincent?
You are passionate about helping organizations drive their success with Data & AI. You feel comfortable operating at the sweet spot between Leadership, Business, and Tech. And, after co-creating a vision and strategy on Data & AI, you’re not afraid to kick-start and drive the execution with a top-notch team that will turn your ideas into reality.
Your passion is data and analytics. You want to create value at our clients by uncovering, organizing, and making sense of data. You understand that it is important to build robust solutions. You feel comfortable to operate in the sweet spot between business and engineering.
You love to help organizations become successful with Data & AI. You have been a practitioner as analyst or scientist. You feel comfortable to approach stakeholders and help them to uncover the needs of their business. And you are not afraid to take ownership and make sure the right solution goes into production.
You are a engineer with a pragmatic attitude. You feel the weight of responsibility that comes with taking systems into production. You easily switch between scripting and structured programming in typed languages. You understand cloud, provisioning and automation. And you know how to build robust systems.
You are passionate about sharing your knowledge and helping others in their development and success stories and feel comfortable explaining difficult subjects on various levels and are adept at creating new learning and development offerings on Data & AI. You are fluent in Python and the most used data science libraries such as Pandas and scikit-learn. Clean code comes naturally to you and you understand why that is important for the next generation of data science products.
We are looking for senior data scientists who feel at home at the intersection between science, mathematics, machine learning, business, and coaching. You have experience in building value from data through ML and software.
You understand ML. You understand that scale is not trivial. You like to code. You are comfortable to be a bridge between data scientists and data engineers to build production-ready, scalable applications driven by data and AI.
