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Software systems engineer job growth summary. After extensive research, interviews, and analysis, Zippia's data science team found that:
The projected software systems engineer job growth rate is 21% from 2018-2028.
About 284,100 new jobs for software systems engineers are projected over the next decade.
Software systems engineer salaries have increased 10% for software systems engineers in the last 5 years.
There are over 141,942 software systems engineers currently employed in the United States.
There are 370,518 active software systems engineer job openings in the US.
The average software systems engineer salary is $107,102.
| Year | # of jobs | % of population |
|---|---|---|
| 2021 | 141,942 | 0.04% |
| 2020 | 274,391 | 0.08% |
| 2019 | 185,984 | 0.06% |
| 2018 | 388,338 | 0.12% |
| 2017 | 364,784 | 0.11% |
| Year | Avg. salary | Hourly rate | % Change |
|---|---|---|---|
| 2025 | $107,102 | $51.49 | +3.4% |
| 2024 | $103,573 | $49.79 | +2.3% |
| 2023 | $101,228 | $48.67 | +1.8% |
| 2022 | $99,441 | $47.81 | +1.7% |
| 2021 | $97,770 | $47.00 | +1.9% |
| Rank | State | Population | # of jobs | Employment/ 1000ppl |
|---|---|---|---|---|
| 1 | District of Columbia | 693,972 | 981 | 141% |
| 2 | Washington | 7,405,743 | 5,722 | 77% |
| 3 | Virginia | 8,470,020 | 5,461 | 64% |
| 4 | Rhode Island | 1,059,639 | 680 | 64% |
| 5 | Vermont | 623,657 | 402 | 64% |
| 6 | Delaware | 961,939 | 594 | 62% |
| 7 | Maryland | 6,052,177 | 3,716 | 61% |
| 8 | Massachusetts | 6,859,819 | 3,944 | 57% |
| 9 | Oregon | 4,142,776 | 2,274 | 55% |
| 10 | Utah | 3,101,833 | 1,618 | 52% |
| 11 | New Hampshire | 1,342,795 | 684 | 51% |
| 12 | Colorado | 5,607,154 | 2,635 | 47% |
| 13 | Wyoming | 579,315 | 271 | 47% |
| 14 | North Dakota | 755,393 | 344 | 46% |
| 15 | California | 39,536,653 | 16,938 | 43% |
| 16 | Montana | 1,050,493 | 443 | 42% |
| 17 | Minnesota | 5,576,606 | 2,268 | 41% |
| 18 | South Dakota | 869,666 | 335 | 39% |
| 19 | Idaho | 1,716,943 | 630 | 37% |
| 20 | Alaska | 739,795 | 277 | 37% |
| Rank | City | # of jobs | Employment/ 1000ppl | Avg. salary |
|---|---|---|---|---|
| 1 | Frankfort | 13 | 47% | $79,104 |
| 2 | Annapolis | 14 | 36% | $91,744 |
| 3 | Menlo Park | 10 | 30% | $137,609 |
| 4 | Dover | 11 | 29% | $89,429 |
| 5 | Lansing | 18 | 16% | $83,496 |
| 6 | Pasadena | 14 | 10% | $126,497 |
| 7 | Springfield | 10 | 9% | $81,456 |
| 8 | Topeka | 10 | 8% | $79,705 |
| 9 | Little Rock | 11 | 6% | $75,579 |
| 10 | Tallahassee | 11 | 6% | $80,086 |
| 11 | Baton Rouge | 11 | 5% | $81,689 |
| 12 | Urban Honolulu | 10 | 3% | $78,088 |
| 13 | Boston | 16 | 2% | $101,758 |
| 14 | Indianapolis | 13 | 2% | $77,275 |
| 15 | Atlanta | 11 | 2% | $81,337 |
| 16 | Washington | 11 | 2% | $96,357 |
| 17 | Phoenix | 10 | 1% | $98,705 |
| 18 | Denver | 9 | 1% | $91,367 |
Hampton University
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Nova Southeastern University
Sepehr Mohammadian: 2. Computer science remains in high demand in today's job market, with California exemplifying this trend. In recent years, the number of open positions in the state has exceeded the average demand rate by 1.5 times. At the University of the Pacific, our CS program is designed to equip students with the necessary skills and experiences to thrive in this landscape. Through our co-op program, in collaboration with recruiters such as Nvidia, HP, and Lawrence Livermore National Lab, students have the opportunity to participate in paid internships lasting approximately 8 months. These internships provide invaluable exposure to real-world work settings and allow students to apply their knowledge in practical contexts and gain valuable industry insights. It is worth noting that many of our graduates choose to return to the same company post-graduation.
Sepehr Mohammadian: 1. This is a pretty broad question. CS degree graduates can engage in different tasks and responsibilities based on the nature of their profession. Examples include 1) software engineering, in which the individual's efforts are toward leading or contributing to software development projects, 2) IT management, where the individual mainly oversees technology strategies and their implementation, 3) cybersecurity, where the individual's responsibilities are associated with the protection of systems and data from cyber threats, and 4) data and AI engineering, where the individual works on machine learning applications and analyze and derive insights from large datasets.
Sepehr Mohammadian: 3. The appeal of computer science among students is often attributed to the relatively short journey from concept to execution. Unlike many engineering fields where hardware constraints can impede the swift realization of ideas, the development of software offers a streamlined process. With nothing more than access to a computer and relative proficiency in programming, individuals can swiftly transform their ideas into tangible solutions. This accessibility and agility contribute to the popularity of CS among aspiring students. On the other hand, CS heavily relies on abstract analysis as a fundamental skill for success. Students who struggle with grasping abstract concepts may find themselves frustrated or disengaged with the field.
Dr. Yohannes Bekele: By entering the computer engineering profession now, individuals can take advantage of the high skilled-power demand in the field, diverse career paths broadly classified under hardware and software sub-areas, lucrative salaries as compared to other fields, continuous learning opportunities, and the potential for entrepreneurship in changing ideas into startup businesses easily. It is a field that offers long-term growth prospects and the chance to contribute to the development of cutting-edge technologies.
Dr. Yohannes Bekele: A computer engineer's daily tasks can be in the hardware or in the software areas. Some common responsibilities in hardware include designing and developing computer hardware components like processors, circuits and memory devices and creating prototypes and testing hardware products to ensure they meet specifications. In addition, analyzing test data and modifying hardware designs as needed is also the responsibility of a computer engineer. For software side, a computer engineer can do writing code and developing software especially focusing on the underlying hardware and interfacing with it such as kernel level programming and debugging existing software programs and ensuring systems run smoothly. Additionally, a computer engineer is responsible for designing and developing electrical systems and components required for computing systems and modification of electrical circuits based on function assessments. For someone entering the field as a junior or new computer engineer, typical daily activities may involve assisting senior engineers, writing code, testing products, attending training sessions focusing on the above mentioned concentration areas, and participating in meetings to learn about ongoing projects.
Dr. Yohannes Bekele: In being a computer engineer, people like all the advantages in the field including attractive compensation packages and lucrative salaries, the intellectual satisfaction of solving complex problems, opportunities for continuous learning and innovation as technology rapidly evolves, ability to work on cutting-edge technologies and contribute to their development and the diverse career paths across hardware, software, embedded systems, and various industries. The main struggle most people have in becoming a computer engineer is its steep learning curve especially when it comes to hardware design and related areas. It takes years to become proficient in the field as compared to other fields such as software programming where a relatively shorter amount of time is enough to join the workforce. In addition, the ever evolving environment with constantly changing technologies, standards, and the need to keep learning new things makes it difficult to achieve the epitome in the field.
Wu-chang Feng: This is subjective, but I think people enjoy the creative act of thinking about a problem, figuring out how to solve it, then building software to do so. What they disliked before was the inability to quickly go from thought to working implementation. This gap is now much narrower.
Wu-chang Feng: I believe so. With the advent of generative AI, it is now much easier to go from idea to implementation. We can now build things closer to the limits of our imagination.
Dr. Sridhar Ramachandran: As a Computer Science graduate, it’s vital to work on independent projects outside of course projects or assigned tasks. This allows you to apply your knowledge and explore new areas and opportunities. Showcasing these projects in a digital portfolio provides a visual and tangible representation of your skills and growth. Emphasizing your attention to clean coding and documentation reflects your professionalism and attention to detail. The field is vast and rapidly evolving, so stay curious, keep learning, and enjoy your professional journey. Avoid getting caught up in fleeting trends. Understanding the difference between work, job, and career is crucial; find work and jobs that contribute to your long-term career aspirations while steadily maintaining your focus on your career goals. In addition, being aware of the organization’s environment and culture at the workplace you intend to work at is important. Familiarize yourself with workplace methodologies like Agile, Just-In-Time (JIT), DevOps, Scrum, Kanban, Lean, Feature-Driven Development (FDD), Extreme Programming (XP), Rapid Application Development (RAD), and Software Development Life Cycle (SDLC) (to name a few). Each organization will have its unique blend of these elements, and knowing what works best for you will help you thrive in your chosen career path. Remember, the key to success in this dynamic field is continuous learning and adaptation.
Dr. Sridhar Ramachandran: To optimize your earning potential in the field of Computer Science, it’s important to establish a solid educational foundation and master widely-used programming languages and technologies. Internships offer invaluable hands-on experience, and obtaining industrial certifications in specialized areas can significantly increase your marketability. Cultivating a robust professional network and honing your salary negotiation skills are also key. It’s important to stay updated with the latest technological advancements, salary trends, and consider focusing on a niche area in high demand. From the outset of your career conversations, it’s beneficial to communicate clear salary expectations. Conduct thorough research on the current market rates for the role you’re targeting to ensure your expectations are realistic. Understanding your worth in the market is crucial, and you should aim for a salary that not only reflects your skills and experience but also keeps you motivated and invested in your work. Remember, while salary is a significant factor, aspects like work-life balance and job satisfaction also play a vital role in your overall career satisfaction. Aim for a win-win salary negotiation where both you and your employer feel the compensation is fair and equitable.
Dr. Sridhar Ramachandran: The field of Computer Science is a dynamic and rapidly evolving landscape. Over the next 3-5 years, several skills will gain prominence. Artificial Intelligence and Machine Learning will be indispensable due to the surge in data generation. Cybersecurity will become critical as our reliance on digital systems intensifies, and it will be everyone’s prerogative to ensure the security of their digital assets. Essential cybersecurity skills will include understanding of network security, proficiency in security software tools, knowledge of threat and vulnerability assessment, and the ability to implement incident response and recovery plans. Proficiency in Cloud Computing platforms such as AWS, Google Cloud, and Microsoft Azure will be sought after as businesses increasingly transition to the cloud. Data Science and Analytics will continue to be pivotal for data-driven decision making. Quantum Computing, though nascent, holds the potential to revolutionize the field. Soft skills like communication, teamwork, and problem-solving will be vital in managing complex, interdisciplinary projects. In this dynamic field, employees who know how to learn, unlearn, and relearn will have a competitive advantage. This is particularly true with the emerging importance for AI programming languages like Julia, Swift for TensorFlow, and Rust.
Sean Walker: Model Based Systems Engineering (MBSE) and Artificial Intelligence (AI) are going to be incredibly important in Systems Engineering over the next 3-5 years. MBSE has already become quintessential to the practice of Systems Engineering, which is why it has become a staple of our Master's and Doctoral programs. AI, of course, is changing almost every technical field and will be important to Systems Engineers as well. For Systems Engineers, the challenge will be understanding how and when to apply AI to solve systemic problems. Of course, both of these elements must be applied with an understanding of sociotechnical systems concerns. An engineer with the skills to apply MBSE and AI without losing sight of the humans in the system will be highly sought after.
Sean Walker: To maximize your salary, it is really essential to learn the tools and methods associated with Systems Engineering while also maintaining a sense of creativity. Employers are not only looking for engineers with the ability to apply specific tools but also the ability to think creatively to solve complex systems problems. I often encourage my students to maintain their creative hobbies so that they don't lose those skills. But, more immediately, gaining a graduate education in Systems Engineering can help any engineer increase their earning potential.
Sean Walker: I think the best advice for a new Systems Engineer, or really any engineer, is to be observant. One of the best things you can do when starting to apply the theoretical aspects that you've learned in school to your new career is to watch and listen to how experienced Systems Engineers practice in the field. This doesn't mean that you can't offer ideas or perspectives that are new, but that there will be challenges in your field that - due to the breadth of Systems Engineering - may not have been covered in your education.
Kin Chung Kwan: Computer science is rapidly growing, with new technologies emerging daily. The desired skill set can vary from year to year. We should always stay updated on the latest global developments and prepare to learn something new. Keeping your skills up-to-date and aligning them with the current needs of employers and target customers is crucial to maximizing salary potential.
Kin Chung Kwan: We are in an Artificial Intelligence (AI) revolution. AI development will continue to be a global priority and dominate the tech landscape in the next few years. For computer scientists seeking career progression, gaining a comprehensive understanding of AI is crucial. Furthermore, understanding limitations, ethical considerations, safety and security measures associated with AI is an important responsibility that every computer scientist should be aware of.
Kin Chung Kwan: Programming is the cornerstone of computer science. Solving problems effectively through proficient programming is a vital key to career success. Learning programming is like athletic training. One cannot become a skilled athlete solely through attending lectures. Programming skills can only be improved with consistent practice. Learning new techniques and repeated practice can help professionals refine their programming abilities and achieve career success.
Nova Southeastern University
Computer Software And Media Applications
Junping Sun Ph.D.: Being capable to perform, being competitive to excel, being able to communicate as a team player, being a connoisseur to act, being a clairvoyance to perceive, being creative to innovate, being conscientious with professional integrity.
Junping Sun Ph.D.: Computer Science and its applications in various fields are very dynamic and constantly evolving, and anyone in the fields needs to prepare to be adaptive by lifelong learning.
Junping Sun Ph.D.: Computer science is an algorithm science for problem solving in real world applications. The skills of problem solving require critical thinking with solid foundation of the professional knowledge in the relevant domains. It is crucial to have strong critical thinking skill with sophisticated logical and philosophical perspectives.
Jonathan Aldrich: Hone your skills so you are great at what you do, and gradually build to be great at what you want to do next. When you are confident in your current position, look for the next step--which may be a promotion in your current organization or a new job outside it.
Jonathan Aldrich: AI is a powerful new tool but it is also unreliable. Learn how you can use it but also what its limitations are, so that you can protect yourself and your customers from those limitations. Always have a way to double-check that the results of AI are sensible and appropriate. No one is a lone coder anymore--you'll be more effective if you can work with other people and with tools that multiply your capabilities. Work on your teamwork skills and keep your eye out for new tools and technologies that make you more effective.
Jonathan Aldrich: Be open to new experiences and focus on learning from them. A degree in computing gives you a foundation but there will be new challenges in every job; always be thinking about what you can do to become more effective at your tasks.
Dr. Jim Huggins: Computer science is a problem-solving discipline. Computer scientists help people solve problems. Typically, those problems deal with data; someone has a large set of data and needs to answer questions about that data, or process it in some way. Computer scientists write programs that run on computers to help their clients answer those questions and perform those processing tasks. On a given day, a computer scientist might do any or all of the following tasks, working alone or in teams: - Meet with clients to understand their problems and how a computing system might help them solve their problems. - Design computing systems to meet client needs. - Build computing systems to meet design specifications. - Test computing systems in order to find errors in their construction and fix those errors. - Repair computing systems that are not functioning properly. - Instruct users how to use the computing systems the computer scientist has designed for them. - Brainstorm new ideas for computing systems that would meet the needs of new customers.
Dr. Jim Huggins: Demand for computer scientists in the marketplace is high right now. The US Bureau of Labor Statistics states that employment in computer science is projected to grow much faster than all other occupations in the next ten years and currently pays salaries twice the national average. Working conditions for computer scientists are generally good: pleasant office environments, with the potential for flexible work environments and flexible schedules. But beyond the economic reasons, choosing computer science as a career means choosing a career that helps people solve their problems. Everyone uses computers to perform hundreds of tasks per day; computer scientists design the systems that people are using to make their everyday life more fulfilling.
Dr. Jim Huggins: Computer scientists enjoy the opportunity to be creative every day. Every computing system being designed is different from the last one or the next one; creativity is required to solve new problems every day. Computer scientists enjoy the opportunity to solve problems. There is a great feeling of accomplishment when a team finishes developing a computing system or helps a client solve their problems by using a computing system they designed. Computer scientists are innovative. By definition, they create systems that never existed beforehand. People enjoy knowing that they're creating the future of our world. Each benefit of being a computer scientist can also be a challenge. Working with people, both to determine the requirements for a system that's never existed, and to build that system, can be subject to the same interpersonal conflicts of any discipline. Problem-solving can be frustrating if the solution is not immediately apparent. Building computing systems requires technical skills that can take time to learn and to master.
Holger Findling: Most companies have a fixed range in salary for new hires. There is very limited space to negotiate a higher pay. It used to be a standard practice not to stay more than three years with a company because salary increases are associated with labor grade ranges. A larger salary increase can be realized by moving to a different company. Typically, 5% increase vs 3% salary increase. However, a programmer needs to continue studying in the field of interest. Earn a master's degree. Be the best you can be!
Holger Findling: Decide what technical area you would like to work in your field of expertise. Do you like to work for the aerospace industry? Decide what specific component you are interested in. Aircraft, Missiles, Energy, Navy - ships, Finance? The issue is that these components are developed in different states. For instance, in Florida Mid-Range missiles are developed and flight simulators. However, aircrafts are developed in Texas, Georgia, and Arizona, not in Florida. There are a lot of programmers needed for financial software. Most likely these jobs would be in New York, New Jersey, Atlanta, California and Massachusetts. In other words understand what industry you would like to work for, and understand that the industries are clustered in different states.
Holger Findling: Technologies are changing very fast, and you must change with it. Don't be rigid. AI is going to increase in the next five years, and the demand for programmers will be high. You would have to take courses studying AI concepts. Bio-Medical fields and Biometrics will be expanding in capabilities and these fields will need a lot of programmers. Take some additional courses, for example Biology and Chemistry.
Eastern Washington University
Computer Software And Media Applications
Dan Tappan: As much as possible, become a subject matter expert in the domain you're working in. The biggest problems we have are in not understanding the customer's problem and not understanding the customer's problem domain. Neither side is conversant in the other's world. We can't expect the customer to learn software development, so we have to learn about their world to bridge this gap.
Dan Tappan: This field changes so rapidly, it's hard to predict. Artificial intelligence has really taken off recently. There's no clear distinction between AI, machine learning, big data, and related areas anymore. They all blend together. These aren't just used as solutions to problems; they're also playing an ever-larger role in the tools we use to solve those problems. ChatGPT, for example, helps in writing documentation, and Google products help in writing code. Solid skills in these areas can streamline the development process.
Dan Tappan: There's not much room for salary negotiation as a new graduate with no experience. Every CS graduate shares roughly the same required background. What often distinguishes one applicant from another, or boosts the salary, is non-required experience with personal projects, contributions to open-source development, and so on. This shows not only applications of the required background, but also the initiative to learn and do more than is expected for the degree.
Northwestern University
Information Science/Studies
David Ostrowski: Create value in your position, become an expert in a few key areas to maximize value, concentrate on deep skill sets within a specific application domain, innovate and push the limits of technology.
David Ostrowski: Keep Learning. Some in the past have held the understanding that learning stops after college. While college gives you the foundation and insight, one needs to continually be learning throughout their career. Maintain an entrepreneurial mindset - even and especially if you plan on working for a large corporation (intrapreneur). Take a portion of your workweek to pursue new ideas and innovate. Maintain a portfolio of your work internally or externally. Love your work.
David Ostrowski: Deep technical software skills, incorporating and innovating with AI, programming languages like Golang, Solidity, Rust, JavaScript, understanding and appreciation of the functional programming paradigm. Innovation and pushing the limits of technology.
Anthony Barrese: Pursue opportunities to broaden your experience across systems engineering, development, integration and test, field sales support and professional services positions. Generalist experience becomes invaluable with career advancement. Running a team is much more feasible for leaders who understand the process behind the work their reports deliver.
Anthony Barrese: There are many paths leading to increased salary potential. Rapidly developing a deep understanding of customer environments and needs can be one of those, but is often not sufficient on its own. Cultivating strong communication skills, building relationships across the business and distinguishing yourself as a leader will all position you for career advancement and the compensation increases that go along with that.
Anthony Barrese: The ability to listen to the customer is the most critical skill. Deeply understanding the needs of the end user ensures business success. In addition, digital engineering environments and digital twin technology in particular, will become increasingly important. These tools enable gains in efficiency and promote enhanced quality.
Dale Dzielski MBA, CMA®, PMP®, SAFe® 4 Agilist: Be prepared for a lifelong learning experience; it just begins now. Be confident in what you know but open to learn more because you will.
Dale Dzielski MBA, CMA®, PMP®, SAFe® 4 Agilist: Enjoying your job is the most important thing for success and longevity.
Smaller businesses usually will pay more but offer the potential to move up as the company grows. Big payoffs can come if the small company that you help to grow sells off to a larger company a few years down the road. You don't have to wait years as this can happen in today's fast pass IT industry in 2-5 years.
Earn a Master's degree such as the WVU Online Master of Science in Software Engineering we offer, ranked #13 in US News, or the MS in Computer Science we offer on campus in beautiful Morgantown, West Virginia. (sorry, I had to put in a plug for our programs) If you don't have the graduate degree when you begin, start as soon as possible as most employers offer some employee benefit, paying for some or for the entire degree.
Dale Dzielski MBA, CMA®, PMP®, SAFe® 4 Agilist: Gain knowledge in Statistics, Data Analytics, cybersecurity, cloud computing, artificial intelligence as well as understanding of Agile Methodology, architecture and design principles/concepts, and development tools such as Jira and GitHub. These will continue to grow in importance to your career. Also, keep watching for disruptive technologies. These will change the way we live and perform our jobs such as the impact AI has already had. I can't name them now because they haven't been innovated or named yet. In fact, you may become a part of doing so.
Jacob Schrum: When it comes to any technology-based field, it is extremely important to be able to learn new things. The tools that today's graduates end up using down the line probably don't exist yet, but there are still foundational skills that are important for graduates to have. The Southwestern University Computer Science program teaches students the core knowledge in data structures, algorithms, programming languages, and more that they need to succeed in various careers related to computer science, but we also give them the chance to do meaningful project-based work that sets them up for career success. This is especially true in the CS Capstone course, which involves meeting with a real-world client, discussing their needs, and then engineering a software solution to meet those needs. This experience allows students to engage with modern tools in an applied context, and requires them to develop the soft skills of communication and negotiation to satisfy the needs of their client.
Jacob Schrum: Generative AI is obviously affecting many industries. Although these systems can write code, this will not eliminate the need for skilled coders and problem solvers. However, those entering the field now can use generative AI systems to quickly write formulaic boiler-plate code, which will give them more time to focus on real problem solving. Systems like ChatGPT, Gemini, and Claude can also serve as interactive troubleshooting tools that can be more effective than searching the web for a specific answer to a very obscure problem. Still, there is ultimately no substitute for having the actual skills to do these tasks on your own. These systems are improving, but they don't get everything right, and they have a major problem with knowing when they are wrong. Furthermore, certain companies and industries don't want their proprietary code disclosed to companies that own these AI systems, and thus do not allow employees to use them. I'll also note that skills not just in using AI systems, but in creating them will be in high demand. Granted, only a few big companies realistically have the kinds of resources to create the models behind ChatGPT, etc, but other companies can either use these models, or make their own much smaller scale models. Furthermore, Machine Learning skills were in high-demand even before generative AI hit the scene, so I would recommend focusing on those skills.
Jacob Schrum: This is definitely not my area of expertise as someone who has mainly been confined to academia for most of his career, but from what I can see, the demand for the skills our students have is still high enough. The main challenge seems to be landing that first job. Once that has been accomplished, it is on the student (now employee) to demonstrate their worth, and keep seeking opportunities to learn and improve. If the company is not giving them the chances for advancement or has a bad working environment, then they should be on the lookout for better opportunities. Granted, there have been some significant layoffs in the tech industry, and that does mean that new graduates entering the market are sometimes in competition with more experienced job candidates. However, the salary expectations of those experienced candidates can make entry-level positions less appealing to them, so there are still opportunities for those entering the field. I suppose this is sort of an unusual way to respond to a question about maximizing salary potential ... I understand that everyone wants to make money, but it is important to be realistic about the job market. Once you have an offer, you can bargain a bit, and you can always be on the lookout for better opportunities, but I think that early on it is a bit more important to gather experience and a steady work record. Ultimately, one will have to weigh the tradeoffs between the opportunities they actually have, and act accordingly.
Lyle Ford: Having a broad base of skills, both technical and interpersonal are very valuable. Often, physics majors are hired to be problem solvers and each problem has its own set of unique conditions that may require a different set of skills to solve. The ability to be an effective team member is vital and proof of that will make you stand out. Evidence of independent work is also helpful so highlight and research or internship experiences you have had.
Lyle Ford: Be flexible and open to new experiences. Technology changes rapidly and your skills will have to evolve to keep up. You will always need your creativity and problem solving skills, but the way in which you implement them will change with your environment which will require you to constantly update your skillset. Always look for opportunities to network. This can give you insights into developing areas and open doors for future paths you may be unaware of.
Lyle Ford: Computer skills (programming, working effectively with AI, and the like) will be important as the world continues to automate. The ability to design, build, and repair electronic and electromechanical systems will also be important for the same reason.
Calvin Deutschbein: The best way to maximize salary in computer science is the same as in any other field - join a union. I would certainly love tech unionization to be stronger but it gets stronger everyday, and for example the Alphabet Workers Union is 1400+ members across various Alphabet (or Google) sites. Individual negotiations or learning certain skills can take you so far, but a group is always stronger than an individual whether negotiating salary or building a new technology. I've never felt better taken care of then I have as a unionized worker, and when I've been between unions I've really felt taken advantage of from salary to benefits to just general workplace pain points.
Calvin Deutschbein: I may be in a bit of a minority on this, but I really believe the next 3-5 years is going to be a good year from programming language theorists. The big push into AI with LLMs has driven, I believe, a lot of confusion over the current state of code automation when in fact existing technologies in program language theory, rather than machine learning, can help push automation much further. I fundamentally believe this form of thoughtful, systematic research is much better than the hype cycle at protecting people's jobs while still adding enormous value to society. LLMs are not particularly good at writing systems code, that's what Rust is for, and I think keeping in mind the difference between buzzwords and foundational technologies would do well for all of us in the coming years.
Mark Whalen P.E.: A system engineer designs, develops, and manages complex technical systems across a large variety of industries. This can include defining solutions to system-level problems, plus allocating requirements, technologies and team member tasking at a project level, as well as communicating complex ideas and systems to key stakeholders.
An entry-level system engineer will typically apply advanced mathematical techniques to solve system-level technical problems, as well as installing, testing, and troubleshooting complex operating systems
Mark Whalen P.E.: Many system engineers enjoy working across all technologies at a higher organizational level, and interacting with all types of technologists to manage and implement complex technical systems.
Many system engineers can feel challenged by their lack of depth of understanding of particular technologies compared to technical specialists.
Mark Whalen P.E.: There are many complex systems in existence or being developed that require knowledge and experience across many different technologies. Also, system engineering careers can often lead to managerial positions like becoming a project manager, operations manager or chief engineer.
Aakash Tyagi: (a) Ability to work at the intersection of AI/ML and vital fields like bioengineering, finance, environmental sciences, Cyberphysical systems, etc., (b) Continual learning and adaptability to changing technology landscape, (c) Critical thinking, problem solving in medium to large team structures.
Aakash Tyagi: Salary potential is truly in the eyes of the beholder. Technical depth of knowledge and skills is quintessential, followed closely by a demonstrated track record of willingness to learn and adapt, and ability to communicate clearly.
Aakash Tyagi: Treat your career as a marathon, not a sprint. Early years in one's career are best spent understanding the technology at its core and what drives innovation. You'll be a great developer and a great leader if your technical fundamentals are strong. This has never been so true than now in the age of generative AI and LLM where creativity and depth of understanding is what will set you apart from others (human and machine).
Dr. Frank Mitropoulos Ph.D.: As you begin your career in Computer Applications, remember that the technology industry highly values adaptability and continuous learning. Commit to staying current with emerging technologies, programming languages, tools, and methodologies. Engage in online courses, attend workshops, and network with other professionals in your field. This dedication to self-learning and the connections you make can lead to job opportunities, mentorship, and collaborations that could shape your future career path.
Dr. Frank Mitropoulos Ph.D.: Maximizing your salary potential as a new graduate with a Computer Applications degree involves strategic positioning, skill enhancement, and effective negotiation. Following are a few strategies to help increase your salary now and in the future: Specialize in High-Demand Areas: Identify and specialize in high-demand areas that generally offer higher salaries. Build a Strong Portfolio: Develop a portfolio that showcases your skills. A compelling portfolio can strengthen your position during salary negotiations. Develop Soft Skills: While technical skills are essential, soft skills like problem-solving, communication, and leadership hold equal significance. Enhancing these skills can give you an edge in negotiations. Do your Homework and Negotiate: Some industries and locations offer higher salaries. Decide what type of industry you want to focus on and do the background research needed to determine whether your skills will help as leverage. Use your portfolio, certifications, and skill set to strengthen your position. Be ready to articulate your value and how you can contribute to the company's success.
Dr. Frank Mitropoulos Ph.D.: As we look toward the future of careers in Computer Applications, several skills stand out for their growing importance. These skills revolve around specific technologies that are expected to continue to grow and evolve. Technologies related to Cloud Computing, Artificial Intelligence (AI), Cybersecurity, and Data Science are quickly evolving and being applied across the technology sector. Cloud Computing: Given the widespread adoption of Cloud services, Cloud computing expertise is indispensable. Understanding how to leverage platforms like Azure, AWS, and Google Cloud is crucial to developing scalable, efficient solutions that meet business needs. Artificial Intelligence: AI and Machine Learning are transforming the world. Skills in these areas to solve real-world problems will be even more critical in the future. Cybersecurity: Digital threats are becoming more sophisticated. Safeguarding data, networks, and systems will require encryption, intrusion detection, development, and regulation skills. Data Science: Skills in Data Science will be increasingly sought after as businesses embrace data-driven decision-making. Extracting meaningful insights from extensive datasets and effectively communicating these findings will be essential. Soft skills: Finally, soft skills such as teamwork, problem-solving, and effective communication cannot be overlooked. Adapting, communicating, and leading will be essential for success.