PCM Vol.2 - Issue 5

that they are also active on the platform. In total we have now
about 13,5 million completed exercises and over 20 million
attempts to solve challenges. That’s huge, right? What is more,
is that we are now at the point where we can get to work with
the best people in academic industry. We have partnerships
with companies like Microsoft and university professors from
top universities like Duke, Princeton, University of Washington
etc.
What are your goals for the future?
I think that there is a lot of room for improvement when it
comes to building up our course library. We would like to add
at least 50 courses by the end of 2016. We also aim to double
the amount of users we have, which means we would like to
grow to 700 – 800 thousand by the end of the year. Eventually,
we want to keep growing the company and find great people
to join our team.
In what way Data Science can have a positive effect on a
company’s performance?
In my opinion it can have an impact on any aspect of the
company. Of course the way in which Data Science might be
used vary depending on the company’s structure and needs.
It certainly will influence the marketing department and help
understand customers better, in terms of their behavior,
needs etc. It will help the sales department qualify leads, as
well as the finance division to detect fraud. Lastly, I believe it
will help the company as a whole to predict the revenue better.
What is the role of Data Science in the future?
It is being still underestimated how substantial it’s role is going
to be. I think that the big transformation in a professional world
is already set in motion. My prediction is that every company
will either have a Data Science department or scientists
managing different teams. The way it will be set up will differ
from company to company but I do think it is going to be
important for every business. Another trend that I expect to
happen is the shift from having an IT department to having a
Data Science department. I predict all this to happen within
the next 5 years.
startup Spotlight
What are your thoughts on the current state of the
industry and what will the most important opportunities
be in this regard?
If the demand of the Data Scientists will grow, then companies
will have to retrain people towards more specific areas. As a
result of that, the education field will grow. Recruiting for Data
Science positions as well, that’s my guess.
Data Scientist has been termed as the sexiest job of 21st
century. Do you agree? What advice would you give to
people aspiring a long career in Data Science?
I definitely agree with that and its not only Hal Varian from
Google who said it but it is being confirmed by other studies
as well. Data Science and applied statistics is definitely a
good choice that will most certainly get you a job and most
certainly will get you a job that’s well paid etc. The demand
for Data Scientists is and will be growing. My advice would
be to focus on learning the skills and focus on learning how
to communicate the results of your analysis. The biggest
challenge is often being able to tell a story and present the
analysis, so that it will be understandable for people with less
knowledge.
Any recent exciting news you would like to share with the
payments community?
We have recently announced DataCamp courses for groups.
It was driven by the fact that many companies need to retrain
existing engineers to become more data literate and get Data
Science skills. The courses allow either professors or people
internally within the companies to teach and train a group of
people and monitor the results of their performance. For us
as a company this is an exciting new step. So far we have had
a lot of success with individuals who want to take a DataCamp
course and ultimately get a subscription to our data course
library. We are also working on great features to make the
tasks even more engaging.
Which of the big data tools will have the biggest impact
in the upcoming years, and why?
I am quite biased in this matter. Even if behind the scenes, the
more advanced technologies like Spark will be used, I still think
that either R, Python or both will remain the bridge between
all new advanced tools. I once heard somebody say that what
HTML did for the web, is what R or Python did for Data Science
- giving people an easy way to interface with data. It’s hard to
predict to what extent Spark and other tools will win over new
technologies, it’s probably going to be a combination of a lot
of technologies. We try to think about what is going to be the
one, two or three languages that everybody is going to use as
an interface to all the other tools. Just like SQL is a standard
to creating data basis. Behind the scenes you can have Oracle
or Microsoft but the interface is SQL.
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