An Alumni at Campus

This week in the Renyi Hour (RH), we had an interesting speaker – Jordan McIver, a BGSE Data Science alumni. He tried to show the class of 2016 what is actually like to be a data scientist in the real world. If you missed his presentation, you can read the interview below, which he gave for the Renyi Hour and have a glimpse of what you have missed. Also, after the article you can find his presentation slides and contact information.


RH person: What do you think is the future of DS (data science)?

Jordan: I think it’s going to be the driver of competitive advantage for most industries. As things become digital, predominantly digital, customers will expect Google-level type of experience.  Every industry that doesn’t have data scientists is going to be disrupted. So eventually, you’ll have industries which are disrupted or industries which now have DS as the driver.

RH person: You talked about data hubs before that. Barcelona is one of them. Why do you think is that? Maybe it’s the location?

Jordan: Well, the big thing is that city council has done a lot. So a lot of investment has been done to make sure it works. If you go to one area of the town, they took all of that buildings and let them be accelerators and incubators. Certainly, Barcelona is a great place to live. And there is general engineering talent as well. But Europe needs more hubs. There is overflow in London and Berlin and they can’t have everything. But I think mostly because of the investment.

RH person: You actually worked in the field of DS before. Why did you decide to have a master in DS?

Jordan: I started in consulting and analysis of data in SQL and Excel, doing some programming. I was learning something and also applying some statistics. I recognized I didn’t know a lot. I needed to get a kick-up. I wasn’t going to learn this things just on my own. Some people can, but I needed to dive into it. Also I managed things I don’t know about. I wanted to be the person who knew the things that manages.

RH person: So know you can say that you know them now? The master was beneficial?

Jordan: Yes, absolutely. I think it’s not going to be an end point. I don’t know other master fields, but potentially the environmental science – you take what you know and then apply it. Here you take what you know, find what you like and then go learn it for real. Especially in the application to the real world. So it’s shifting how it works. If you are expecting to come out of it and not have to know a lot more, it’s going to be tough. But if you want to find something you like, it’s great. Finding your area, having a happy life that also you’ll be successful in.

RH person: What did you want to be when you were a small child? I think DS wasn’t it?

Jordan: I wanted to be like a sports player, like a hockey player

RH person: What will be your advice for the class of 2016?

Jordan: Be grateful for all the knowledge you are presented. Learn the most of it. Really, break your back and try to learn from the great people you have here. And realize that this is the one year of your life that you’re not working, so find your own way, find what you want to do. Just become like data evangelist for yourself. And meet as much people as possible. You won’t have time to go to meetups, have a beer with people and get up late. Go do it NOW, because when you start a job, it’s going to be a lot more difficult.


Jordan McIver contact information:



PRESENTATION: BGSE_Valtech_Agile_Data_160205

Personal Approach

Big_data   The moral from last Wednesday’s Renyi Hour is the “personal approach.” The main message which Alberto Barroso del Toro: Senior Manager Advanced Business Analytics, and Alan Fortuny Sicart: Senior Data Scientist, from Indra Business Conculting is:

“Cuando haces preguntas aleatorias obtienes respuestas aleatorias” ROBERTO RIGOBON Sloan University MIT.

English translation: “When you get random questions, you get random answers

So although we are dealing with big data which of course means enormous data quantity, variety, etc. the most important part is not to look at it just as random facts or digits. You need to understand the business, to get to know the field. Only then you can ask the “specific” question, seek for the “specific” answers and hopefully see how to optimize the process. To be successful researchers need not only the usual package of data analytics skills but also they should leave their comfortable chairs, “get dirty” and explore the business filed.