You can find a lot of different career paths under the computer science umbrella. It’s an incredibly diverse field that ranges in focus, specialties, and job roles. Understanding all the different job titles and purposes is crucial for deciding which path you’d like to take on your journey to learning computer science. Each job will have similarities and differences that may determine which suits your desires and passions more. For instance, you can pursue a computer science education and become a Software Engineer, where your main focus is developing software. In this role, you’ll write and work on code, debug programs, and maintain functionality. The day-to-day tasks of a Software Engineer will vary greatly from that of a Data Scientist, which is another common role for computer science professionals to pursue. In this role, you’ll find yourself engaging in data analytics far more frequently. Additionally, you’d be tasked with using models and advanced algorithms to determine trends from said datasets. You can also work in cybersecurity, which differs greatly from a Software Engineer and a Data Scientist. As a Cybersecurity Engineer, you will detect, mitigate, and prevent cyber attacks on various levels. All in all, different job titles will not only define the nature of the work but also dictate what specific skills you need. Computer science jobs are wide-ranging and abundant, so it is worthwhile to consider all the various avenues this educational journey may take you on.
What is a Computer Scientist?
A Computer Scientist is a professional who applies their technical and analytical skills, as well as the key principles of computer science, to solve problems and develop new technologies. They work on a variety of projects that range in purpose, from designing models and developing software to analyzing datasets and enhancing the functionality of a computer system. Additionally, they are frequently found researching new ideas and contributing to the betterment of an organization or specific product. Computer science is a wide-ranging field, so many Computer Scientists typically acquire skills in programming, artificial intelligence, and cybersecurity. All in all, they play a crucial role for any company that relies on computers, data, software systems, and other technical products to keep their day-to-day operations running smoothly.
Computer Scientist Skills
Technical Abilities
To become a computer science expert, you will first need a diverse skill set, ranging from technical to soft skills, to fix complex computer problems and develop new innovative technologies. You’ll need to acquire astute technical capabilities that go beyond simple computer mastery. This includes vast knowledge of programming languages like Python, Java, SQL, C++, and JavaScript. In addition, database management is a key skill that enables a computer science professional to maintain and manipulate large datasets. The average computer science expert will also be skilled at understanding and using algorithms, developing machine learning models, and understanding the core of artificial intelligence including concepts like neural networks, natural language processing, computer vision, and other AI-driven tools.
Specializations
Because computer science is such a broad field, many computer science students may choose to study more specialized skills. These skills are ingrained in computer science specializations such as software development, cybersecurity, and web development. You may want to sharpen your software engineering capabilities by learning to use version control with Git and design, test, and maintain different software systems. On the other hand, many computer science experts learn to handle cyber attacks like fraudulent banking activity. Expertise in securing a network and encryption methods can be incredibly worthwhile. Web development requires full-stack development knowledge, which is also a common skill many computer science experts learn.
Soft Skills
Just as important as the technical skills are the plethora of soft skills a computer science professional will want to attain. This will include problem-solving, as a Computer Scientist will have to creatively solve complex technical issues and debug different errors. In connection with problem-solving, they will need to be strong critical thinkers with an analytical mindset. For a Computer Scientist to thrive in their work environment, they will likely need to have a collaborative personality and be able to adapt to numerous situations and changing project requirements. They are typically meticulous to ensure they make as few errors as possible during their projects. Plus, they will need to be skilled in the art of communication as they will work closely with other professionals in and outside their departments.
Computer Scientist Career Path
The path to becoming a Computer Scientist will look different for each person, but the overall expectations start with obtaining an education. For job acquisition, you will want hands-on experience that ensures you feel comfortable with complex concepts, tools, and techniques associated with your computer science specialty. Plus, you’ll want a training method that offers additional benefits and resources. This combination can lead to landing an entry-level position where you can gradually accumulate experience, define your forte, and forge a path to a successful and enjoyable career.
You may start as a generalized Computer Scientist or specialize in artificial intelligence, cybersecurity, machine learning, data analysis, and many other roles. For instance, you could start as a Cybersecurity Analyst and work up to Chief Technology Officer. You may begin as an entry-level Machine Learning Engineer and find yourself climbing the ranks to become a senior-level employee. With more time spent in the field, you will become more knowledgeable about the more complex concepts and capable of handling large projects.
Once you feel confident and capable in the field, you may feel prepared to explore other computer science career options. For instance, you can explore the many freelance opportunities as well. Freelancers have the flexibility to work from anywhere and for any company, which allows them to diversify their portfolio and expand their skill sets. This path leads to more opportunities and helps push you to the next level in terms of creativity, innovation, and technical expertise. Moreover, it enables you to adopt a broad range of skills that sharpen your business acumen, including self-discipline, client acquisition, project management, and other business operations. Each computer science professional's path will look somewhat different, but this is part of the appeal of working in this field.
Machine Learning Engineer
What is a Machine Learning Engineer?
A Machine Learning Engineer is an expert in designing, developing, and deploying machine learning models. They specifically use algorithms and statistics to help computers predict trends, make decisions, and learn as they continue to operate. This involves developing and deploying models that can handle natural language processing, computer vision, and predictive analysis. They work with programming languages, computer models, machine learning frameworks, and other tools for handling datasets, building models, and maintaining machine learning systems.
Similarities with a Computer Scientist
Machine Learning Engineers are similar to Computer Scientists in several ways, namely in their use of programming. They both need a strong understanding of algorithms, database management, and computational problem-solving. Both roles also handle research and developmental tasks essential to solving complex problems and developing new models. However, Computer Scientists are in a much broader job position than Machine Learning Engineers, who specialize in data and machine models.
Machine Learning Engineer Job Skills
Some key skills a Machine Learning Engineer would need include knowledge of programming languages (like Python and R) as well as machine learning libraries and frameworks (like TensorFlow or PyTorch). In addition, they will need strong data analysis and management skills and the ability to visualize data in different forms. They will also frequently use cloud platforms like Azure to deploy their previously designed machine learning models.
Industries That Hire Machine Learning Engineers
Machine Learning Engineers are hired in all kinds of industries, ranging from technology and automotive to healthcare and finance. Across each industry, they will likely perform both similar and dissimilar tasks. For instance, financial Machine Learning Engineers may utilize their skills to detect fraud in the system. On the other hand, healthcare Machine Learning Engineers can create models that depict patient outcomes and develop treatment plans. Those in the automotive industry may use them to develop self-driving vehicles. In the tech industry, a Machine Learning Engineer will likely have a broader range of responsibilities, like model development, customer experience, and statistical analysis.
Average Salary for a Machine Learning Engineer
Salary reports vary depending on numerous factors such as location, specialization, industry, experience, and education level, but data from Indeed suggests the average base salary for a Machine Learning Engineer in the United States is roughly $161,000. Most entry-level positions are on the lower end, but with high-level jobs, the salary expectations could easily surpass $200,000. Plus, your location plays a huge part. New York City-based Machine Learning Engineers earn roughly $186,000, whereas those in Chicago earn closer to $162,000.
Data Analyst
What is a Data Analyst?
Data Analysts are professionals who manage and analyze large datasets to provide insights and support throughout the decision-making process. Their tasks include interpreting data-driven insights, building reports, visualizing their findings, and using various tools to assist them in their analytical procedures. In addition, a Data Analyst will work with databases, software, and various methodologies to reveal trends and patterns in datasets. All in all, their goal is to translate data into a language everyone can understand, which lends itself to optimized business strategies and operations, thus increasing productivity and profit.
Similarities with a Computer Scientist
Data Analysts share foundational knowledge with Computer Scientists, including data management, statistical methodologies, and programming languages. Some of their tasks overlap such as using tools and software to analyze data and visualize their findings. However, Computer Scientists focus mainly on development and design, whereas a Data Analyst is immersed purely in the data management side of business operations. Still, they are similar enough that the two roles can sometimes appear interchangeable or at least work closely with one another.
Data Analyst Job Skills
Some of the most important skills a Data Analyst needs include expertise in data management, visualization, and analysis. This includes understanding programming languages like SQL and Python as well as software and tools such as Excel, Power BI, and Tableau. Moreover, a Data Analyst must understand how to present information clearly and understandably and possess well-developed communication skills. They should be able to identify what message the data is sending and communicate the actionable insights that can be gained from it.
Industries That Hire Data Analysts
As companies grow increasingly reliant on data for their daily operations, Data Analysts can find employment in virtually any industry. They are frequently hired in marketing departments to assess and predict consumer behavior and needs. Finance, healthcare, retail, and technology companies are all known to hire Data Analysts to manage data from marketing campaigns, financial reports, and project outcomes. Specifically, a Data Analyst may help retailers manage their inventory or assist in improving patient care by examining trends in healthcare data. The opportunities for Data Analysts are practically endless.
Average Salary for a Data Analyst
Glassdoor reports that the median total pay for a Data Analyst in the United States is around $108,000. However, many see salaries ranging from $87,000 to $137,000. Of course, this varies greatly depending on experience and education. For instance, you may start on the lower end of the pay scale, but by advancing from an entry-level Data Analyst to a Senior Data Analyst, you can expect to earn closer to $133,000 to $197,000. Companies such as Meta, Wish, and Affirm offer salaries within this range, so it’s worth comparing roles by city and company before deciding on a position.
IT Security Specialist
What is an IT Security Specialist?
An IT Security Specialist is responsible for maintaining the safety and integrity of an organization's computer systems. They safeguard highly sensitive data by implementing preventative measures to detect and block data breaches. An IT Security Specialist plays a critical role in identifying and responding to security threats in real time. They are hired across various industries and are typically granted access to confidential areas of an organization’s digital infrastructure.
Similarities with a Computer Scientist
IT Security Specialists share relevant skills with Computer Scientists despite differences in their focus. Both roles require strong knowledge of programming, computer systems, and algorithms, enabling them to understand complex technical challenges. They also conduct research and debug systems regularly. However, while Computer Scientists focus on developing and improving systems and models, IT Security Specialists are focused on protecting systems against security threats and implementing security protocols.
IT Security Specialist Job Skills
An IT Security Specialist should understand advanced network security techniques, firewall management, and security software systems. This includes knowing when to apply various encryption methods and how to scan for fraudulent activity. They should also be familiar with industry-specific compliance standards. Additionally, knowledge of automation can be beneficial for handling repetitive or time-consuming security tasks more efficiently.
Industries That Hire IT Security Specialists
Any industry that depends on technology hires IT Security Specialists. This includes healthcare, finance, entertainment, technology, retail, and both federal and local government entities. In government roles, specialists protect highly sensitive national security data. In the healthcare industry, IT Security Specialists help ensure that patient treatment plans, diagnoses, and personal health data remain secure and confidential.
Average Salary for an IT Security Specialist
Indeed reports that the average salary for an IT Security Specialist in the United States is approximately $112,000 per year. However, this can vary significantly by location. For example, specialists based in New York City and Los Angeles earn around $135,000 and $134,000, respectively. In contrast, those in Washington, D.C. earn closer to $122,000. The specific industry and employer also affect salary expectations.
Software Engineer
What is a Software Engineer?
Software Engineers develop, test, and regularly upgrade software applications. They apply engineering principles to ensure software operates efficiently, reliably, and at scale. A Software Engineer typically ensures that applications are scalable, meet user needs, and function as intended. They use various tools and techniques to build software for mobile devices, web browsers, video games, and streaming platforms.
Similarities with a Computer Scientist
Software Engineers and Computer Scientists share foundational skills, including proficiency in programming, software development principles, debugging, and algorithms. While Computer Scientists address a broader spectrum of computing problems, Software Engineers focus more specifically on designing, building, and maintaining software systems. Despite this difference in scope, both roles utilize similar tools and methods.
Software Engineer Job Skills
Programming is one of the most essential skills a Software Engineer must master. Common languages include Java, JavaScript, Python, and C++. In addition to coding, they must also work with related libraries and frameworks. Software Engineers are responsible for testing, updating, and maintaining applications to ensure they remain functional and up-to-date. This requires strong problem-solving abilities and analytical thinking, along with creativity to build user-friendly and efficient software.
Industries That Hire Software Engineers
Software Engineers are employed across a wide range of industries, including finance, healthcare, entertainment, and technology. Many are hired by tech companies to build custom applications or platforms. In the finance sector, Software Engineers often create secure, user-friendly banking applications. In entertainment, they may develop video games and interactive multimedia experiences, playing a vital role in shaping gameplay and user experience.
Average Salary for a Software Engineer
According to Glassdoor, the average base salary for a Software Engineer in the United States is approximately $115,000. However, with additional compensation such as bonuses and stock options, earnings can be significantly higher. Salaries vary based on education, years of experience, industry, and company. Entry-level roles offer lower pay, while Senior Software Engineers can earn well over $200,000 annually. High-paying industries include finance, pharmaceuticals, biotechnology, entertainment, and insurance.
Web Developer
What is a Web Developer?
Web Developers are responsible for designing, building, and maintaining websites and web applications that are both functional and visually appealing. Their work ensures a smooth user experience and supports the business goals of the website such as increasing traffic and revenue. Web Developers typically specialize in front-end, back-end, or full-stack development, which involves both client-side and server-side programming.
Similarities with a Computer Scientist
Computer science professionals can become Web Developers, as both roles share many of the same foundational skills. These include an understanding of programming, software development principles, and algorithmic logic. Both also work with databases, though their usage may differ. The main distinction lies in focus: Web Developers concentrate on building websites and web applications, while Computer Scientists may work on a wider array of systems, software, and models across various platforms.
Web Developer Job Skills
Web Developers blend technical expertise with creative skills. For front-end development, they typically use HTML, CSS, and JavaScript, while back-end developers often rely on Python, Ruby, PHP, or Node.js. Full-stack developers work with both. In addition to coding, Web Developers must understand responsive design, user interface (UI) principles, and user experience (UX) considerations. Many also use tools from the Adobe Creative Cloud to align a site’s visual design with the brand identity.
Industries That Hire Web Developers
Virtually every industry that maintains a web presence hires Web Developers. This includes education, retail, finance, healthcare, media, and entertainment. While all developers focus on building effective websites, their specific goals vary. For example, a Web Developer at an educational institution may focus on ensuring accessibility and usability for students and staff, while one working in retail may emphasize smooth ecommerce functionality and on-brand visuals to increase conversions.
Average Salary for a Web Developer
According to Indeed, the average base salary for a Web Developer in the United States is approximately $80,000. Many developers also receive bonuses averaging around $2,500 annually. Location significantly influences salary expectations. For instance, Seattle-based Web Developers often earn up to $134,000, while those in Chicago average around $103,000. Los Angeles salaries are closer to $93,000, aligning more closely with the national average. These differences often reflect local demand and industry presence.
Why Become a Computer Scientist?
There are many reasons to consider becoming a Computer Scientist. This field opens the door to a wide range of professional opportunities and is rapidly evolving. It offers access to high-paying jobs suited to individuals with strong technical skills, critical thinking abilities, and a passion for solving problems. With specializations such as artificial intelligence, digital systems, software engineering, cybersecurity, data management, and web development, computer science is an exciting and versatile career choice.
In addition to its wide range of specializations, computer science offers flexibility in job type and industry. Professionals can transition between fields, work for small businesses or large corporations, and pursue remote, hybrid, or freelance roles. Career advancement is achievable through continued education, certifications, and practical experience. Any company that relies on computers or data will require a computer science team, making the field highly adaptable to personal interests and career goals.
Moreover, computer science careers are generally lucrative. Many professionals earn six-figure salaries, especially in high-demand specialties and locations. As technology continues to grow and integrate into all aspects of life and business, the demand for skilled computer science professionals will only increase. If you have strong technical skills, enjoy creative problem-solving, and want to contribute to innovation and advancement, a career in computer science may be an ideal path.
Learn the Skills to Become a Computer Scientist at Noble Desktop
The Noble Desktop Data Science Certificate enables students to learn everything required to enter the field of data science. The curriculum covers a range of topics, including statistical analysis, machine learning, and data visualization. Students will gain experience using Python, R, and SQL, and they’ll develop skills relevant to predictive modeling and visualization tools. Through hands-on projects, students will build a professional portfolio and gain the confidence needed to apply their skills in the workplace. This program is designed to provide a strong foundation in data science and prepare students for an in-demand, evolving career path.
Likewise, Noble Desktop offers a Python for Data Science Bootcamp, where students learn how to use Python for data science tasks such as data manipulation, analysis, and visualization. The bootcamp includes training in popular libraries like Pandas, NumPy, and Matplotlib. Students will work with Jupyter Notebooks and complete real-world projects that demonstrate their Python proficiency. This hands-on training is ideal for learners seeking professional-level skills and practical experience.
If you’re more interested in JavaScript than Python, Noble Desktop also offers a JavaScript Programming Bootcamp. In this course, students explore the uses of JavaScript and learn its syntax, functions, and programming capabilities. The curriculum includes writing and debugging code, manipulating the Document Object Model (DOM), and handling browser-based interactions. Understanding JavaScript enables students to build responsive and dynamic web pages. This bootcamp is a great entry point for learners who want to establish a solid programming foundation and grow their web development skills over time.