3 Types of Computer Science Skills Every CS Professional Needs

Industry Advice Computing and IT

Computer science is an increasingly popular field, and with good reason. Society has come to rely on the technology created by this industry to fulfill the functions of daily life, resulting in both exciting career opportunities and above-average salaries for individuals who choose to pursue a computer science career.

While the job outlook remains overwhelmingly positive, the evolution of the computer science field over the last few decades has created a demand for professionals with more than just basic coding skills. Now, professionals looking for success must have a strong combination of technical, interview, and soft skills unique to this specific sector.

Read on to explore what traits, skills, and subject matter fall into these three categories, and how a master’s degree from a university like Northeastern can help aspiring computer scientists hone them all.

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Whether you have a technical or non-technical background, here’s what you need to know.


Top Computer Science Skills to Learn

1. Specific Technical Skills

The most commonly acknowledged type of skills required among computer scientists are the practical abilities that allow them to develop software and digital tools. Some of the top skills in this category include:

  • Programming: This incorporates deep knowledge of algorithms and data structures, and coding skills in languages like Java, C, Python, and JavaScript. Those hoping to improve their coding skills specifically should consider pursuing formal training in the form of a graduate degree or bootcamp.
  • Software development: CS professionals should possess knowledge of software development and engineering principles, including the software development process from start to finish—writing programs using popular program languages, testing for usability, and ultimately implementing the programs.
  • Mathematics: Alongside a comprehensive understanding of mathematical theory—which is equally as vital for aspiring CS professionals to obtain—knowledge of statistics, calculus, linear algebra, and other advanced mathematical techniques are mandatory for individuals in this field.
  • Data Analysis: Basic data analysis skills are important for computer scientists, as data plays a key role in many advanced CS practices, including artificial intelligence (AI), predictive analysis, and more.
  • Data Visualization: As crucial as it is to be able to analyze data effectively, it’s also essential that CS professionals can properly visualize data and results in a way that stakeholders can understand. This includes translating raw data into graphs, charts, and other visual tools to help communicate findings.
  • Ethics: As technology continues to advance—especially with tools like artificial intelligence and machine learning—professionals in this field must develop an understanding of ethics and its impact on computer science.

The above list of skills includes only the baseline requirements for generic roles in the CS field. Those who wish to specialize in a certain niche area—such as AI, data science, cybersecurity, etc.—or plan to apply their computer science skills into a specific field will need to expand their knowledge in those areas, as well.

Honing Your Practical Skills With a Master’s Degree

One of the most efficient ways to gain these industry-specific skill sets is through the pursuit of a master’s degree in computer science from a top university like Northeastern. In a program like this, students participate in an array of courses designed to provide both the in-depth knowledge and hands-on abilities needed to thrive in this ever-changing industry.

“We really try to balance theory and practice [in our programs],” says Ian Gorton, director of the computer science master’s programs at Northeastern University—Seattle. “[We want] graduates to have a deep enough education theoretically so they can keep up with advances and changing technology, but also have the practical skills needed to get a job and thrive professionally.” 

Northeastern’s MS in Computer Science curriculum is strategically designed to expose students to both computer science theory and practice. Courses like advanced software development, for example, cover advanced system design and solution-building, while simultaneously providing students the chance to practice explaining their solutions through “code walk-throughs.”

“[A code walk-through] is a common industry practice in which people stand up and explain their solution to an instructor…and then get questioned about it,” Gorton says. “This is obviously good interview practice, but also breeds a rigor in people that gets them thinking about how to solve problems.”

Learn More: Is a Master’s in Computer Science Worth the Investment?

Other courses focus on building software individually or as part of a small team to solve bigger problems. In these scenarios, students “work together to try to solve problems and build a solution,” Gorton says. Through this process, “they learn principles about how to split up a solution so that multiple people can work on it at the same time, and how they can plug the resulting components together and make it all work” the way they might as part of a future engineering team.

This type of hands-on learning also extends outside of the classroom in Northeastern’s programs. Through experiential learning opportunities, students get the chance to explore real-world problems for organizations that are a part of Northeastern’s expansive partner network.

“In our advanced software engineering course, we basically form a team of about 20 people, and we build a solution to a real problem…[for] an external stakeholder,” Gorton says. “It’s always a really tricky problem and requires teams to work across campuses to build a solution.” 

Did You Know: Northeastern offers advanced computer science degrees at seven of our regional locations, including Arlington; Boston; Oakland; Portland, Maine;  Seattle; Silicon Valley; and Vancouver.

Northeastern’s program also embraces the need for students in this field to have certain interdisciplinary skills that allow them to apply their technical knowledge to other industries. In fact, Northeastern’s Align MS in Computer Science program is specifically designed for students from a non-computer science background. In this program, students first learn the foundational CS skills they would have obtained in pursuing an undergraduate CS degree and then advance to the more complex topics covered in a master’s degree. These individuals graduate with advanced CS knowledge that complements their existing expertise in another sector and will allow them to change careers to computer science.

Students with or without a background in computer science also have the opportunity to declare a computer science specialization while enrolled in Northeastern’s master’s in CS programs. In doing so, they have the chance to learn an array of other relevant, practical skills that they can use in pursuit of specialized roles. For example, students who declare a specialization in AI might explore more advanced data science topics, as well as statistical modeling, natural language processing, machine learning, and more.

Gorton explains that, while specializations like these can be useful in setting professionals apart in competitive job markets, most will likely start their career in CS with a much broader role. For this reason, Northeastern strategically incorporates a balance between core skill sets and those explored in a specialization. “You have to have a good broad portfolio of skills and then have a specialization that you can kind of pull out of your pocket when you need to,” he says.

2. Relevant “Soft” Skills

Soft skills are considered those which are not tactical, technical, or tied directly to a specific career path. Emotional intelligence, leadership, and innovation are common examples of these kinds of traits, which are gained through hands-on experience and are valued across industries

While technical skills were often thought of as the core of functioning workplaces in the past, businesses today now consider “soft skills” to be equally—if not more—relevant. Below, we explore the top “soft skills” that computer scientists should obtain.

  • Critical Thinking: Being able to identify a problem, analyze the details of the situation, and then formulate an effective solution is an incredibly important aspect of computer science work.
  • Attention to Detail: Effective computer scientists must be able to pay close attention to detail, as their work is often complex, demanding, and requires a keen eye.
  • Creative Problem Solving: Solutions to many of the problems computer scientists are tasked with solving are not always obvious, and instead require these individuals to think outside of the box.
  • Communication: Communication is a key soft skill in most industries, and computer science is no different. Professionals in this field must be able to communicate effectively with their teams, their bosses, and their stakeholders—including using data to tell stories and share insights.
  • Listening: Tied to the need for proper communication skills is a need for computer scientists to be good listeners. Professionals should be able to listen to people’s problems and establish the necessary context from those conversations to solve them. This is especially important when CS specialists work with industries they’re not particularly familiar with.
  • Collaboration: Despite common misconception, computer scientists very rarely work in isolation. In fact, more often than not, they are required to operate as part of a team, either working with other computer scientists to reach a solution or develop a product, or working with other members of a larger business team on a project. Either way, developing the skills needed to work as part of a larger group is essential to a computer scientist’s success.

Honing Your Soft Skills With a Master’s Degree

Taking the time to develop these soft skills can go a long way in setting aspiring computer scientists on a path toward success. Many of these abilities can be obtained through real-world experience or the pursuit of a Master of Science in Computer Science degree at a top university like Northeastern.

Many of the courses Gorton mentions have been designed to hone students’ practical skills in Northeastern’s CS programs also simultaneously provide opportunities for students to develop many of these integral skill sets. Courses that require students to stand up in front of their professors and peers and complete a code walk-through, for example, allow them to sharpen their communication skills. Similarly, courses in which students work as part of a team allow them to practice collaboration, listening, and leadership. By incorporating real-world problem solving into coursework early on—and providing countless opportunities for hands-on learning within functional workplaces—Northeastern also gives students the chance to practice critical thinking, creative problem solving, and more. 

Graduate school provides a unique opportunity for aspiring computer scientists to acquire these vital skill sets alongside more technical ones, and develop themselves into well-rounded professionals.

3. Interview Skills

When pursuing a new role in any industry, applicants should work to develop their interview skills. This might include preparing for your interview by doing research on the company you’re interviewing with, prepping your answers to commonly asked questions, or even practicing maintaining eye-contact during a conversation.

In certain industries, however, there is more to an interview than a simple series of questions and answers. In the computer science field, for instance, an interview often includes an in-person presentation and a descriptive explanation of your work in which applicants answer in-depth questions about how they reached their solutions. An interview in this field may also require applicants to display certain examples of their live projects via a portfolio and to speak at length about the success of that work.

In order to prepare for this unique type of interview, Gorton identifies a few key skill sets that aspiring CS professionals should work to hone beforehand.

Presentation Skills

“There is a whole sort of ritual for a technical interview these days,” he says. “You have to not only be able to answer [an interviewer’s] questions, but you have to also know how to communicate your solution.”

In order to do this, an interviewee will be asked to write out a problem on a whiteboard and describe the thought process as they work to solve it. While the act of problem-solving should likely be second nature to those in this field, this interview task often feels more daunting to those without proper presentation skills. “You have to explain what you’re doing as you go along and engage the interviewer in a dialogue,” he says. “You don’t just want to turn around and start writing on the board for five minutes.”

To sharpen this skill, Gorton suggests practicing this process a few times through before each interview to ensure you are comfortable both with your actual mathematics work and your presentation abilities. “You’re probably not going to get it right the first time,” he says, emphasizing that practice makes perfect.

For this reason, Northeastern’s programs “spend a lot of time working with students on those sorts of technical problems and getting them not only to understand their solutions on a technical level, but [also] how to communicate them properly,” he says.

Portfolio Building

While computer scientists may not utilize a print or online portfolio to display their work the way professionals in other fields might, it is still important for them to know how to properly share their work in an interview if asked.

Gorton explains that prepared CS professionals will either link to live projects or show examples within code repositories online. “When we write solutions, we put them typically into something called GitHub, and you make your GitHub code or profile public so you can cite it on your resumé and show the projects you’ve contributed to.”

Setting You Up for Success: Having the ability to properly integrate coding examples into a resumé is an essential skill for computer scientists, but many computer scientists who are just starting out don’t have live examples of their work to share. To help build this portfolio of work early on, Northeastern’s master’s in computer science programs give students dozens of opportunities to practice their work hands-on through experiential learning opportunities, group projects, in-class work with real-world external stakeholders, and more. 


Networking is a pivotal part of any interview process, no matter the industry. Today, 85 percent of all jobs are filled through this practice, and the computer science field is no different. The positive, professional connections aspiring CS professionals make through their time in graduate school or in the workforce have the ability to set them apart during interview processes—especially when it comes to applying to top tech companies like Google, Facebook, or Amazon.

For this reason, individuals need to take the time to learn how to properly make and maintain relationships with those in the industry. Northeastern’s graduate programs in computer science, for example, offer opportunities for students to attend university-hosted events, collaborate with industry professionals, and make real-world connections with those in their field through time spent working hands-on with leading organizations.

Pursuing a Master’s Degree from Northeastern

Whether you are looking to break into the computer science industry or are hoping to advance your career, a master’s degree from Northeastern University can help. Both the master’s in computer science and Align master’s in computer science programs are designed to help aspiring professionals obtain the technical, “soft,” and interview skills needed to thrive in this industry, all while under the guidance of leading industry professionals. Grow your network, build your resumé, and start your career off right with a master’s degree in computer science from Northeastern.

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