This post was written at the request of datsciawards.ie, presenting awards to the top Data Scientists in Ireland for 2017. I’m not nominated, but you should definitely check out the excellent people who are.
They’ve also partnered with UCD Michael Smurfit Graduate School of Business to give a full scholarship for the Masters of Business Analytics for 2017/18 to an EU student. If you’re thinking about a career move into Data Science, I can strongly recommend the course. More information is available here.
At the beginning of 2015, due to a prolonged downturn in the oil price, I was given a years leave of absence from my job as a Drilling Engineer in Norway. I was scheduled to go on vacation around the time I found out, so before I moved my life from Norway, I had two weeks to think about what to do next. The way I saw it I had three options:
- Get another job in Oil and Gas, or try and move into another field;
- Go back to college and get a new set of skills; or
- Travel, explore and party;
There weren’t really any Oil jobs going at that time, and I didn’t feel like rushing back into work anyway (despite the downturn we were very busy in Norway, until we very much weren’t). Travel would’ve been great, but left me in a precarious position if there was not a job for me at the end of my year off.
That left college, which then begged the question: What to study?
I was forced to think about what it really was about my job that I enjoyed, and I realised that the most challenging and enjoyable projects I had worked on all involved data manipulation and processing. At that time, I didn’t know Data Science was a thing, but reading up on it really opened my eyes to this new world, and I realised that this was where I wanted to be.
My introduction to Data was when I was 14, and taking part in an after school maths challenge class. I remember struggling with every question that involved calculus (which was all of them), but one time I got to use Excel, and with my dads help, built a model which correctly solved the problem! I was hooked.
Throughout the rest of high school, and my undergraduate degree, my interest in how data moved and related within a model was my driving curiosity, though I never realised it was something I could do full time.
I studied Chemical Process Engineering at the University of Western Australia, and my skills with manipulating data relationships helped tremendously in building financial and processing models for my final year project and thesis. I interned at various engineering and financial institutions, and at the time thought I wanted to be a M&A analyst.
Upon graduation, I weighed my options and opted for adventure, taking a technical offshore engineering position with Schlumberger Ltd, based out of Stavanger, Norway.
My role with Schlumberger was far from Data Science (I was an offshore engineer involved with drilling and logging new wells), my interest and skills in data analysis held me in good stead. When I was asked to turn some data output from a new product into a well-site visualisation for our customers, I dived into Visual Basic and got my first taste of programming. Recording macros and learning from Microsoft forums got me pretty far, and I ended up building software to automate a previously manual task and opening up a new revenue opportunity for Schlumberger.
One of the many amazing views I got to experience in Norway
With skills and experience in hand, and the decision to study Data Science, the UCD Michael Smurfit Graduate School of Business stood out for it’s academic focus (as opposed to a coding bootcamp or such), and prestige in Ireland. I applied and was accepted to the MSc Business Analytics.
The first semester was focussed on building a solid foundation of Maths, Statistics, and Project Management skills. There wasn’t as much of a focus on programming initially, but the advantage of taking the course full time was that we had ample time to develop these skills in our own time. As the semester went on, we worked in teams to build a Black-Scholes option pricing model, and explored and critiqued IT project management philosophies.
We also gained a solid academic review foundation, and spent the winter thoroughly exploring an area of literature.
The second semester saw the focus shift from theoretical to applications of algorithms. Some of the projects I’ve undertaken include:
- Deploying Dijkstra’s and Bidirectional Variants for finding the shortest path through a network, using optimised data structures;
- Developing an algorithm to appropriately assign aeroplane seating;
- Simulating a new viral advertising model to increase click rates on Facebook;
- Undertaking a clustering case study to optimise children’s T-shirt sizing; and
- Suggesting appropriate ordering of Formula 1 races to minimise travel time for drivers.
The biggest drawcard of the course for me was the opportunity to spend the summer working on an industry partnered project. I’m working on an application to display and summarise the Irish housing sector, to aid Data Scientists at AIB when providing insights.
The summer practicum gives us an opportunity to apply the skills we’ve learned over the last year. Mine involves Python, Django, Javascript, D3, web-scraping, cloud computing, SKLearn and the Google Maps API.
Working with D3.js animations to show changes in house prices around Dublin
The course itself has been thoroughly worthwhile, and I’ve improved my academic understanding of algorithms and approaches, vastly increased my coding ability, and have a wide range of tools available to me to solve many problems.
The course has also given me plenty of scope to improve my skills in areas around Data Science, such as learning Django to quickly deploy web apps and dashboards, D3 to visualise data, and cloud based data processing to push computational possibilities beyond my personal resources.
I’ve also had the opportunity to take place in 3 Hackathons, each of which opened my eyes to areas which I needed to improve my skills in:
- The ESB Big Energy Hack taught me the necessity of knowing your data before focussing on a solution, as well as the difficulty of balancing multi-disciplinary teams;
- The AIB Datahack showed me that while my data cleaning skills were improving nicely, I needed more practical experience in Machine Learning; and
- The Citadel Correlation One Datathon taught me that Data Science is as much about the question being answered as it is about the process (our solution was very business focussed, whereas the winners went for more interesting insights).
At the Correlation One Datathon
The Correlation One Datathon was a great culmination of skills, and showed how far I had come since the beginning of the course. In 6 and a half hours, we parsed 15gb of data and put together a model for Uber to optimise the distribution of drivers across New York at any point in time. As an extension of this, I explored a much larger subsection of the data to figure out which neighbourhood partied the hardest in New York.
The social side of my time at UCD has also been a highlight, with diverse classmates, all of whom have welcomed me to Ireland. The highlight of the social calendar was the Smurfit Ball.
I’ve also had the opportunity to represent UCD in Ultimate Frisbee, traveling to Belgium to compete in October, and placing 2nd in the Irish College Championships in April.
It’s been a great year at UCD, and a great (if slightly roundabout) journey into Data Science. I’m really excited for all the opportunities I’m going to have to deploy the skills I’ve learned.
I thoroughly recommend the UCD MSc Business Analytics course and really encourage budding data scientists to apply for the scholarship!
Good luck to all nominated for the Irish Data Science Awards in 2017!
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