Dutch hockey sensation, Paul Melkert, is an example of such a profile. Having played professionally alongside the five degrees he’s earnt, his background in Web Science and Big Data Analytics, alongside Industrial Engineering & Computer Science, render him particularly adept to understand the ever-evolving waters of technology. Pair that with a deep interest in financial markets and the application of tech mechanisms, and the Fintech industry is a brilliant match.
We sat down with Paul to discuss his time playing premiership hockey, both in Holland and the UK, and how he is now keen to apply his skills and knowledge developed at university to the Fintech space.
What’s your earliest memory playing hockey?
I would have probably been about 6 years old. I mostly played football and golf at that age but I would quite frequently tag along with my father who played at the local hockey club. I remember dabbling in playing with a ball and stick whilst he would play his games. It was not until a few years later that I formally started playing hockey at club level but I have very fond memories of those Sunday afternoons at my father’s games.
What would you say is your greatest achievement within the sport?
That would be winning the first Dutch national championship in Hockey Club Rotterdam’s history in 2013, 10 years after becoming a member of the club as a junior. I am incredibly proud to be part of that history.
What makes hockey different from other sports?
I think that what sets hockey apart from other sports that require a high level of hand-eye coordination and good footwork, is that hockey might be (one of) the most dynamic and quickest team sports out there.
What characteristic do you believe is the most influential to your success within sport? Has that carried over into other areas of your academic/professional career?
I truly believe that love of what you are doing or learning to do is the basis for success. So having had the opportunity to sample a range of different sports (e.g. football, golf, tennis, hockey) when I was younger allowed me to find out what matched with my personality and interests. The deliberate and consistent practise required for success in sports then becomes more natural. Finding my match through sampling a range of different things before specialising has definitely carried over into my academic career as well – the field of systems engineering and industrial engineering introduced me to a variety of different disciplines before specialising in machine learning at University College London.
Melkert Scores Dagger Goal For Hockey Club Rotterdam in Playoff Final
What have you learnt most from the game?
I have always found it interesting to see how different personalities had very different ways of communicating in high-stress situations (e.g. high stake game). The experience of being a team member of a multicultural group of professional athletes, working alongside others in the pursuit of excellence, has demanded effective communication skills, which are transferable to any environment.
You’ve managed to maintain playing hockey at a premiership level whilst obtaining multiple degrees, your latest being a MSc in Web Science & Big Data Analytics from UCL, how have you managed it all?
My latest and final academic degree I can assure you! It is true that the rigorous schedule of training and competing as a professional athlete alongside the dual commitment of studying has required detailed planning, the ability to prioritise and delivering against deadlines. Mostly, it has always been about finding a healthy balance between studies and sports with one being prioritised over the other depending on the time of year – leading up to and during playoff time, all focus would be on hockey and on trying to reward ourselves for all the hard work we had put into training and games throughout the season. Off-season would allow me to catch up on studies and enjoy other facets of life.
Where did your interest in computer science stem from?
I did an introductory programming course at some stage and that sparked my interest. I remember completing the course and I had a lot of questions that would be answered by pursuing the direction of computer science ultimately leading up to my specialisation in machine learning.
How did you come in contact with add-victor?
add-victor approached me a couple of years ago on LinkedIn. I had heard good stories about add-victor from Harry Martin (with whom I played hockey at HC Rotterdam) but it was not the right time back then for me to come to London. I stayed in touch with add-victor anyway and when I started the post-graduate programme at UCL last September, Steve and I met for a coffee.
What would you say is the most valuable resource add-victor can offer student-athletes?
I think add-victor has something to offer at pretty much any point in a student-athletes’ transition from sports to a professional career – whether that is guidance in defining a student-athlete’s career aspirations or providing student-athletes with a possibility to have a chat with a potential employer. For me personally, I had a pretty good idea of what kind of role I aspired (a tech role in finance), but it was thanks to add-victor’s network that I had an opportunity to sit down with people from the FinTech company I am about to start.
You’re about to start a new role within a fast-growing FinTech company, what are you most looking forward to?
I am really looking forward to kick-starting my professional career and in particular the role within the company – the role will require both the breadth from my systems engineering / industrial engineering background as well as the depth from my background in machine learning.
What would you say is the most interesting element of the FinTech space?
Disrupting the traditional financial service industry using open-source technologies really appeals to me.
Where do you see the FinTech space going over the next decade?
In my opinion, machine learning, and artificial intelligence in the broader sense, will define the world’s foremost technological frontiers in the next decade. So I think we will continue to see an increase in the adoption and systematic integration of machine learning and artificial intelligence in the FinTech space over the next decade. When adopting these techniques at scale though, instances of unfairness and bias in the use of artificial intelligence will become an important issue in any industry, including the FinTech space.
If there’s one piece of advice you could give to an aspiring athlete looking to go into FinTech, what would it be?
More of a general advice: no matter how rigorous the schedule of training and games is, try to sample a range of different academic and professional experiences before specialising. This will make you more flexible as well as more certain about your transition from sports into any industry.