Data Science Career Talks - Nuria Oliver
Updated: Nov 14, 2019
IADSS will reach notable personages of the Data Science world and talk about their careers, analytics & data science teams they manage and their advice for young professionals in this area. Hamit Hamutcu firstly reached Nuria Oliver, PhD for an interview. She is the Director of Research in Data Science at Vodafone, as well as a member of the IADSS Advisory Board.
Please note that you can read the interview transcript here, or watch it directly from our IADSS YouTube channel. Please follow our channel to stay up-to-date with our latest interviews and news from IADSS Research:
Hamit Hamutcu: "Okay. All right, here we are recording with IADSS Advisory Board Member Nuria Oliver. To begin with, could you provide a brief intro on your current role and a few highlights from your past experience?"
Nuria Oliver: "I'm Nuria Oliver, and I have a PhD in machine learning and artificial intelligence from MIT. My area of expertise is human behavior modeling from data using statistical machine learning techniques. I am the director of research in data science at Vodafone, and also chief data scientist in an NGO called Data Pop Alliance, whose goal is to leverage AI and data science for social good, and I'm also a chief scientific advisor to a think tank called the Vodafone Institute."
Hamit Hamutcu: "Talking about your roles at Vodafone and Data Pop Alliance, what kind of roles do you interact within the data analytics space and how do the career paths and responsibilities look like for these roles, can you give a couple examples?"
Nuria Oliver: "In my work, I interact with a lot of data scientists and a lot of different profiles who have a passion for drawing meaningful insights from data, which I would say is sort of like the main role of a data scientist. They come from different paths, from different career paths, given that data science traditionally hasn't existed as a degree. A lot of the people are computer scientists and many of them have a PhD or a masters in artificial intelligence or data analytics, sort of related fields. Some people are physicists and they study physics, even a PhD in physics do a lot of quantitative analysis. Some other people come from engineering and they have different types of engineering degrees. I would say those are the three main degrees."
"Within data science there are also different roles. The main role, which is the role that I lead and I've been working on is a research role, so it's research in data science. I work with a lot of PhD's on relevant topics, but there are also the vast majority of the data scientists in more applied roles, where the goal is to help institutions, big corporations or public administrations to leverage the vast amounts of data that they have, non structured data, using statistical machine learning techniques to make better decisions or to personalize their services to be more efficient or to make predictions."
"A very important related role which cannot be underestimated is the role of the data engineer. All the data that we're talking about has to be stored somewhere and it has to be analyzed, usually stored in large distributed storage systems, and analyzed using distributed computing. There are significant efforts by what we call data engineers who are people who have stronger backgrounds on the engineering and computer science, kind of lower level technical knowledge, who are in charge of enabling all the necessary infrastructure to be able to carry out the necessary analysis."
Hamit Hamutcu: "Okay, perfect. Then maybe a word of advice to an aspiring data scientist, what would you advise to someone who wants to start exploring the data science career?"
Nuria Oliver: "Yeah, so there are lots of professional opportunities in the data science field, because there are many more and much bigger demand than offer, mainly because data science hasn't existed as a degree until now. I always encourage people it's never too late to learn about this field. There are many high quality online courses that people can take from reputed universities or from Coursera or Udacity and so forth that are very helpful. If someone doesn't have a bachelor's degree, some universities are already offering bachelor degrees in data science in different countries in the world, so that could be another path. Even if you have a degree, you can do a nano degree or some kind of online degree to really get up to date with the main techniques that we use in data science. I would like to encourage anyone, and particularly women, because this is definitely a fascinating field with loads of opportunities and we really have the opportunity to shape the world and move towards a more evidence driven, data driven, decisions making world, which I think will be positive for all."
Hamit Hamutcu: "Okay, perfect. This was great. Thanks so much. I think it obviously shows that you spent a lot of hours talking to people about this, so it comes out as very natural."
Nuria Oliver: "Oh thank you, thank you very much, well I just talk a lot in general :)"