Data science as a career option is gaining immense popularity. According to Statista, the global big data market will reach around $64 billion by the end of 2021. 

Data scientists are in high demand in both the U.S. and the U.K. The 2020 emerging jobs report from LinkedIn featured data science as one of the top three jobs in the U.S. and number seventh in the U.K.

Candidates looking to make a career in data science are often confused regarding the degrees they should pursue to begin working as a data analyst. 

Those working in the data science field don’t all hold the same qualifications. Several different degrees can open doors to a career in data science.

In this article, we will discuss the type of degrees that you can opt for to make a career in data science and also find out the different skills needed to further your data analytics career.

Let’s start!

Types of degrees that you need for a career in data science

1- Mathematics and statistics

You can opt for a degree in mathematics and statistics to become a data scientist. Most jobs often require you to be familiar with statistics. Strong knowledge of linear algebra, calculus, measure theory, probability theory, analytical geometry, and differential equations are also required.

2- Computer science 

A degree in computer science builds up your knowledge of coding. Besides, programmers are good analytical thinkers. By completing your computer science degree, you gather exceptional programming skills, which is a top skill for most data science employers. 

If stats are to be believed, over 18% of data scientists major in computer science. You can get yourself a computer science degree and acquire knowledge in SQL, Python, R, Tableau, and other programming languages. Good programming knowledge saves a lot of time, and employers readily hire people with a computer science background for the data scientist role.

3- Physics

A degree in Physics is helpful to become a data scientist since you actually learn to model things. Physics requires you to learn mathematics and polishes your real-world problem-solving skills. Physics enables you to explore a wide range of mathematical, analytical, and programming skills. Therefore, a degree in Physics is an excellent choice for starting your career in data analytics. 

4- Engineering

If you love engineering and are obsessed with data science, you can opt for a graduate degree program in data science and engineering. Under this degree, you will build your foundation in programming using Python or any other programming language. You will also learn different statistical methods for decision making and explore several machine learning techniques such as linear and logistic regression. 

5- Business analytics (Master’s of Science in Analytics degree)

Business analytics helps to turn data into actionable insights. Under the business analytics program, you will learn different modules such as data analytics and decision making, accounting analytics, principles of management science, and marketing analytics. The focus remains on data analysis. Therefore, a business analytics degree is perfect to begin your career as a data analyst.  

6- B.S. in data science

A bachelor degree in data science lets you prepare for a rewarding career in data analytics. The B.S. degree is a comprehensive program covering principles of statistics, predictive analytics, forecasting analytics, linear programming, data visualization, regression analysis, R programming, Python programming, financial risk modeling, and risk simulation. 

Besides, you will get a chance to work on real-world data science projects and collaborate with companies to obtain hands-on experience. An undergraduate degree enables you to build a solid foundation for your data science career. 

What other types of skills/knowledge do you need?

No matter whatever degree you choose to pursue, specific essential skills are needed to build a successful career in data science. 

Here are the must-have skills required to become a data scientist:

  • Fundamentals of data science: A strong foundation in machine learning, artificial intelligence, and data science are needed to become an expert in this field. 
  • Programming languages/coding: Python, R, and Julia are some of the programming languages you need to master. 
  • Data visualization: A data analyst should be able to build a story out of data. Data presentation is crucial to present the data understandably. Histogram, bar charts, waterfall charts, and pie charts are some of the data visualization techniques that are useful. 
  • Artificial intelligence/machine learning: It is one of the core skills that you should have to build predictive models. Knowledge of advanced logistic regression models such as CatBoost, XGBoost, and Random Forest are vital. 
  • Critical thinking and problem solving: Besides having the finest mathematical and programmatic skills, you should have exceptional problem-solving skills. You should know the correct method to solve a problem because then only you will be able to prepare algorithms that follow the best approach to find a solution. 

What type of career paths can you follow in data science?

There are different career options to choose from once you acquire the required degree and skills to further your career in analytics. Here are some of the top career paths in data science:

  • Data architect
  • Data scientist
  • Data engineer 
  • Enterprise architect
  • Machine learning engineer
  • Data analyst
  • Business analyst
  • Business intelligence developer

Final Thoughts

Data science is an in-demand career with strong job prospects. As a data scientist, you need to work on collecting large sets of data, build algorithms, analyze different data sets, and present them in an easy to understand format. If you enjoy working with numbers and stats, data science is the perfect career option. Pick a degree of your choice as mentioned in this article, constantly upgrade your skills, and continue learning new technologies.