Should I pursue a masters in data science as an Economics graduate? If this is a question that has bothered you, you are at the right place. This blog covers the topic Why and How to get into Data Science with economics degree.
Data Science career has been an overlooked option by many economics graduates because of lack of awareness. Huge demand for this field has been seen from 2014 onwards and it has been one of the fastest-growing industries.
The major demand in data sciences is for data scientists, statisticians, data analysts, bankers are to name a few.
What is Data Science?
Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Data science is a broad field that includes many subdivisions such as data preparation and exploration; data visualization and presentation, analysis, etc.
Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data.
Today, successful data science professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.
Why should you Get into Data Science with Economics Degree?
The job market for the data science sector has seen massive growth in the past few years. This sector has seen a massive hike of 650% than the other industries and this is just the beginning of the growth of this industry.
Economics students have a better understanding of social –studies that can be added as an additional perspective to the data and skills. With their microscopic understanding of society, they can think beyond just numbers and make impactful decisions.
Related Article: Masters in Social Data Science & Public Policy Analytics
As students of Economics, they learn a lot more about Psychology, Politics, Finance, Mathematics, and Statistics. Hence, the approach of an economist’s student is always interdisciplinary.
Since they already learn econometrics – Linear regressions and Logistics regressions, they already have a basic understanding of machine learning.
Economics is one of the top 5 majors for pursuing Masters in Data Science
The analytical skills provided in Economics may lack the mathematical rigor compared to programs like physics and mathematics. However, a degree in economics provides one with business skills, that are essential in the real-world application of data science. Read best degrees for a data science career.
One big advantage of Economics is that it is a very strategic and often different way of thinking of problems and how to solve them.
Top Careers in Data Science with Economics Background
Data analysts are required for highly analytical, inquisitive jobs. A few of the sectors where data analyst is required are pharmaceuticals, manufacturing, consulting, finance, education.
As an analyst, you are required to gather data, evaluate and provide insights as to how the data can be used to further improve the business and make better decisions.
MARKET RESEARCH ANALYST
Market research analysts compile huge data and figure out strategies to help the organization market its service or product in the best possible manner.
A data scientist uses algorithms, artificial intelligence, machine learning, and many other statistical tools to turn data into meaningful information that can be used by large organizations to improve their business strategy and hence improve sales.
With the combined knowledge of economics and data science, a powerful contribution can be made to the country’s monetary policy and strategies can be laid that can help in the growth of the economy.
How can I get into Data Science with Economics background?
Approximately, 13% of current data scientists have an Economics degree.
- If you want to get into data science after graduation, you can go for entry-level jobs in data science.
- A master’s degree at the top universities will require at least 2 years of experience in data science.
- At least 3-4 years of experience in the data science field is required to ensure success in this field.
How to Begin the Journey of Getting into Data Science with Economics Degree
Start taking extra courses/modules – especially, math classes such as calculus, linear algebra, statistics, and probability, as well as programming classes too.
The best way to start is to learn the 3 Bibles: Python, R, and SQL. These are enough to make some nice projects. And they are all open-source (free!)
There are of course many others but typically there are 3 areas of data science:
- Statistics: R, Matlab,
- Databases: SQL, SAS, Excel, NoSQL
- General math and back end languages: Python, Java, Scala
Now there is a new subcategory:
- Machine learning: Tensorflow, Torch, Pytorch
Focus on the 3 for now and move up to the higher-order languages to do even cooler stuff!
Read the detailed articles on how to become a data scientist and How to Get Data Engineering/Science and Deep Learning Jobs.
List of Top Universities that Offer Bachelor Degrees in Data Science with Economics
- University of Chicago
- Drexel University
- Northeastern University
- University of Kent
- University of Southampton
What do Universities look for in MS Data Science Applicants?
As college students, you already have a few subjects in your curriculum to provide you with a base for data science. Econometrics is one such subject that forms the basis to understand machine learning models. Hence subjects like econometrics, statistics, mathematics should be taken seriously and conceptual understanding is a must.
Second, on the list is learning a programming language. Even if you have not learned any programming language, now is the best time to start learning one. You can start with Python or R.
OTHER TECHNICAL SKILLS
SAS, statistical and mathematical skills, storytelling and data visualization, Hadoop, SQL, machine learning.
Internships are a great way to learn about any interests. You can take up an entry-level internship and learn more about Data Science. You can understand if you want to pursue data science further.
Here is a list of 10 companies that offer internships for Data Science:
- Hewett Packard
You can also do a few courses from edX, Coursera, or other platforms to understand different concepts. A few of them are:
- Professional Certificate in Data Science [edX]
- Analytics: Essential Tools and Methods [edX]
- Applied Data Science with Python Specialization [Coursera]
- Data Science A-Z™: Real-Life Data Science Exercises Included [Udemy]
- Introduction to machine learning for data science [Udemy]
- Machine Learning [Coursera]
- Data Science Path [Codeacademy]
- Data Science Specialization [Coursera]
- Programming for Data Science [Udacity]
- Statistics with Python [Coursera]
These are a few most popular courses and not an exhaustive list. You can do your own research do other courses as well. Feel free to look at our curated list of best online courses on data science and machine learning.
Apart from these skills, you also need to work on your soft skills. Soft skills include Communication Skills, Life Long Learning skills, Presentation skills, Adaptability, and problem-solving.
Top Universities for Masters in Data Science Abroad
In the UK:
- University of Edinburgh
- Kings College of London
- Imperial College London
- Anglia Ruskin University
- Lancaster University
- University of Bristol
- University of Birmingham
In the USA:
- Stanford University
- Harvard University
- Yale University
- University of Pennsylvania
- John Hopkins University
- UC Berkeley