Open-Source Internship opportunity by OpenGenus for programmers. Apply now.
In a world that is rapidly adopting new technologies, it’s no surprise that computer and information scientists are in high demand, with their employment rates projected to grow by 22% from 2020 to 2030. The US Bureau of Labor Statistics notes that some 3,200 yearly openings on average are expected to result from the need to replace workers who transfer to different occupations or exit the labor force. Although computing researchers share a similar education and career path with information systems managers and computer programmers, they have a specific subset of skills and duties that set them apart.
Computer research scientists are charged with advancing the field of computing by developing new computing-based techniques, repurposing older solutions to work in specific contexts, and studying emerging technologies for any problems that may occur. Computing researchers explore topics like artificial intelligence, big data, machine learning, edge computing, quantum computing, robotics, cybersecurity, and bioinformatics. For this year's tech trends, they're concerned with the real-life applications of Metaverse, cryptocurrencies, and 3D printing as well. To begin with your career as a computing research professional, here are some things you’d need to do:
Build requisite know-how
The work of computing research is difficult, and it’s best suited with people who have analytical minds. To succeed in this field, you’d need to have advanced knowledge of high-level mathematics, programming languages, logical reasoning, software engineering, algorithms, and data structures; generally, you would need a master’s or Ph.D. in computer science and related fields to meet industry standards. Many researchers also have additional education in sister disciplines, like physics, which would help when studying aerospace or quantum topics. Other researchers opt instead to specialize in emerging technologies. Maybe you want to hone your expertise in data science to support industries with day-to-day and long-term decisions. You’d need to have further studies on machine learning models, data visualization, data cleaning, and data analysis to be effective in the field.
Examine potential career paths
As analytical people, most computer research scientists have realistic expectations for their prospective careers. Still, you can have a positive outlook as nearly every field needs to tap into computing to solve complex issues alongside global technological transformation — and there are few doctorate-holding computer scientists to go around, so you’re likely to be in high-demand. While you can opt to take an academic career path, many professionals go into the workplace to work on practical projects. You can begin with an entry-level position as a third-party consultant or an in-house specialist. Once you progress and gain experience, you may move into a management position at a large firm.
Polish your soft skills
Computer science may require a lot of practical knowledge, but soft skills are still essential because you’ll be working with other people wherever you go. Some of the most important soft skills to have include agility, communication, creative, and emotional intelligence, which are all necessary in a highly stressful field. This is why it would be beneficial to identify the transferable soft skills you have. By doing this, it will allow you to assess your strengths and weaknesses, so you can work to improve any gaps. Create a plan for learning and improvement, maybe through courses on that soft skill or through guidance from a mentor. Asking for constructive feedback from colleagues and loved ones can further push you to develop these soft skills.
Keep an eye out for new opportunities
Given that computer science itself is a fairly new field that constantly branches out into new technologies, there are plenty of opportunities to further your career. Academic projects, immersive workplace internships, and computer science competitions allow scientists to push boundaries on their work. For instance, recent experiments on AI machine capabilities have puzzled computer scientists and philosophers alike; currently, theoretical calculations show it would likely not be possible to control a super intelligent AI, but you may discover something that could change our understanding. Career opportunities are endless when you proactively explore ways to improve existing systems or ideate original solutions to both new and old problems.
