Economics and data science (with The University of Manchester)
In this episode of Future You, Ralf Becker tells us about the MSc Economics and Data science at The University of Manchester and the careers it can lead to
Participants
In order of first appearance:
- Dan Mason - editorial manager, Prospects
- Ralf Becker - professor of economics and deputy head of department
Transcript
Dan Mason: A new course at The University of Manchester combines the traditional academic discipline of economics with cutting edge data science. Skills that are highly sought after by prestigious employers. Find out more in this episode of Future You
Dan Mason: Hello and welcome to Future You the podcast from graduate careers experts Prospects. We're here to help you achieve your career goals. My name is Dan Mason. And in this episode, I talked to economist Ralf Becker from The University of Manchester about a new Masters course they're launching the MSC Economics and data science. Studying on this program, will see you tackle real world economic issues using up to date skills including coding, potentially setting you up for a career in government, central banks, the private sector or academia. Don't forget to subscribe to Future You in your podcast app, and head to prospects. ac.uk for any careers and study advice. But in the meantime, here's more about that course.
Dan Mason: I'm joined for this episode by Ralf Becker, Professor of Economics Education at The University of Manchester and one of the course designers of the MSC economics and data science. Ralf, welcome to the podcast. Thanks for joining us.
Ralf Becker: Good morning, Dan. Thanks for having me.
Dan Mason: So just to start with, before we get into more detail about the course, tell us about what economics and data science is because I understand this is an emerging field.
Ralf Becker: Yeah, sort of both are long existing fields. So I'm an economist, I can certainly tell you a lot about economics, economics is really the social science which tries to understand how individuals or groups of people or companies or even governments, how they behave and what impact their behavior has on the outcomes in the economy, like economic growth, or unemployment, or inequalities. And so it actually turns out that even in economics, there has been a long tradition of dealing with data as sort of a subfield which we call econometrics. But very recently, there has been this sort of emerging field of data science or machine learning, which has come from the computer science tradition. And colleagues in that area have developed sort of a range of new technologies and mechanisms, and models that help us deal with particularly huge data sets. And also some sort of unstructured datasets, like text data, which traditionally economists have not been working with. And so now there's this combined field emerging, where econometricians are economists and data science scientists work together to basically bring the best of both worlds to the table and tackle really interesting questions.
Dan Mason: Let's turn now specifically to the course at The University of Manchester, the MSC economics and data science. So what would you say are the courses unique selling points? What makes this course standout?
Ralf Becker: I think the key standout selling point here is that this will be a small course, we're thinking of having between 20 and 30 students max, that means that the students will have or develop a very close relationship not only between each other, but also with the teaching staff on the course. And that will enable us to help students to really get hands on experience with their computing skills. And that we think is super important that once they come out of the job, that they have really strong skills. We will also ask students to work together in groups and do lots of the main coursework together because that is just the standard way how people have to work in the industry, very rarely will you be sitting, locked away by yourself to do something you will always have to achieve things together with other people. And to facilitate that there will be a range of skills, like for instance, GitHub, how do you use sort of an online platform to cooperate when you write code together, and we will help students to master these sort of very important employability skills in that area.
Dan Mason: And so what type of students will you be looking for to apply to this course and to take on this course?
Ralf Becker: This is perhaps also a special aspect of this program. We really need students who have had deep exposure to economics. So we are mainly thinking of students who have had an undergrad economics degree, whereas many other programs in data science also at The University of Manchester, are sort of open programs where students from a range of different disciplines can come to the program. So here we need students to have a deep understanding of economics already. But increasingly, in undergrad programs, we in Manchester, but also at other universities, we are helping students to learn how to deal with data. And what we want is the student whom the data bug has bitten, who have realised during the undergrad degree, this is like super interesting being able to deal with large datasets and using them to answer interesting economic questions. And it's those students who are curious about how we use data to answer interesting economic questions, which you want to have on this program.
Dan Mason: I understand that another of the highlights of this course is the plans for guest speakers, I wonder if you could talk a little bit about the types of guest speakers that students can expect to hear from?
Ralf Becker: Yes, well, we're having a particular unit in this program, which will run throughout the entire years where we on a weekly basis meet for the students and they do sort of practical things, practical coding exercises, and into these meetings we will have a range of guest speakers coming and talking to the students about the type of problems they are dealing with in their organisations. The program is still in a year ahead so we don't have particular names yet. But the people we've been talking about with this program, and you've sort of indicated interest to supporting this are people for instance, from Ofcom, or the ONS or government departments business energy and industrial strategy, but also private institutions like an energy retailer on meta or Google and these are sort of all colleagues who realised there's a shortage in the right sort of skills in the industry who are very keen to talk to students about potential job opportunities, but also in first of all, the type of problems they are dealing with.
Dan Mason: Yeah, and you mentioned there the issue of skill shortages in these areas. And if we could take a bit longer now to talk about that aspect, which is how this course is going to help students become employable. So what are the skills that they're going to be learning? What are the types of careers that you expect students to be able to move into by studying this course? Because I think that's the key thing that potential applicants will want to know about, where's this course going to lead for them?
Ralf Becker: Yeah, absolutely. We expect students wanting to come out of this program with a range of opportunities at their hands. The type of jobs we're looking at here are jobs in exactly the sort of institutions I just mentioned, in terms of our guest speakers. There will be a range of government institutions, government departments, but also like the Bank of England or central banks in other countries, which have a deep need for people with very thorough data skills to help them answer the questions that is interesting, that are of interest to the particular departments, government departments. There's also roles in regulators. There's a whole range and every country has whole range of different regulators. And increasingly, regulators are using very large data feeds, data sets, to observe how companies, media companies, how they're behaving, in order to investigate further behaving according to the set of regulations set out to them. And for all of these jobs, what it requires is people who not only have the skills of the data scientists, but can combine that with the knowledge economists will bring to the table to understand how to structurally think about the behavior of individuals or institutions. So these sorts of government or sort of government type of institutions like central banks, or regulators, I think, are certainly a prime field of employment for students here, but then equally private institutions. These days, companies like meta or Google or Amazon are actually the largest employers of economists. And the type of economics that's of interest to these is usually driven by the availability of an enormous amount of data. Think about the amount of data Facebook or meta is sitting on in terms of the information they have about their users equally, Amazon, which knows, you know what individuals want to purchase, or are looking at. And not to mention Google, of course, who probably knows more about each of us than we can imagine. And the use of this sort of data requires both the technical skills of knowing how to deal with the data and how to use the data. But it is made easier if you're also bringing the skills of an economist to the table.
Dan Mason: Well, it sounds like there's going to be a huge range of exciting opportunities for graduates from this course then. So if we move on then so as people, anyone listening to this, they might be thinking of applying to this course. What advice do you have for them? Are there things that you think they should be doing now to prepare ahead of applying? What advice do you have for people who might be considering it?
Ralf Becker: The best advice is perhaps to be curious and to just keep your mind open for interesting questions and think about how could we use available data to answer these questions, but in terms of practical things students could do in advance to this particular course or other similar course of courses. Really practice, practice your data skills, practice your coding skills, in most undergraduate programs, you will get an introduction in how to code with R or with Python, which are the two languages we will use in this program. But of course, in an undergraduate degree, the amount of tuition you can get there will only lead you so far. So what you can really do is on your own account, or together with some friends, to sit together and deepen your skills. And there's lots of ways to do that as coding is really one of the skills which we cannot teach you, we can help you we give you some guidance, where we're perhaps put the ladder in front of you, but you need to do the climbing here. And you can do a lot of that independently. And it will be one of the skills realistically, that is sort of quite difficult. So the better prepared you come, the easier it will be once you are in the program.
Dan Mason: That's fantastic advice. Thank you for that. And so just to finish off, then, is there anything else you want to say about the course that we haven't covered already?
Ralf Becker: No, I think we covered most. Most of the things I'm really already I'm super excited to sit together with the students which we will have to think together with them about interesting questions to answer, students will have the opportunity to, to basically set their own research questions and to follow them up as part of a group work assignment, which we will ask them to do, but then also as part of your dissertation, because we understand every student will come with different motivations to this program, different questions that are in their head as being the most important challenges of our time. And we want to give students the opportunity to adjust the research parts of their program, to their own needs and questions. And I am super excited together with my colleagues to sit together with students and find out what are the questions that makes you want to study on this program? And how can we help you direct your research part of the program into the direction that helps you research that question?
Dan Mason: That's brilliant, and I'm sure after listening to you talk about it will be some potential students excited to get started with it as well. Ralf, thank you very much for your time today.
Ralf Becker: Thank you very much, Dan.
Dan Mason: Thanks very much to Ralf for his time and for that insight into the new MSC Economics and data science at The University of Manchester. Head to the university's website for more information on applying or follow the link in the episode description. You can search for other postgraduate courses by going to prospects.ac.uk. To hear more from Future You find us on Spotify, Apple podcasts or wherever you listen to podcasts, and get in touch with comments, feedback or suggestions. Just email podcast@prospects.ac.uk. That's it for this episode. Thanks for listening and we'll see you soon.
Note on transcripts
This transcript was produced using a combination of automated software and human transcribers, and may contain errors. The audio version is definitive and should be checked before quoting.
Find out more
- Read all about The University of Manchester's MSC Economics and Data science.