ACM CareerNews for Tuesday, January 19, 2021
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Volume 17, Issue 2, January 19, 2021
As companies scramble to adapt to a tight IT job market, they are doing whatever they can to attract top tech talent. For some that means getting a head start in filling the most in-demand roles, which include data-focused and security-related positions, according to the Robert Half Technology 2021 IT salary report. The survey also reveals the average salaries for each role based on experience. While many factors will impact a starting salary, including competition, location, corporate culture, and budgets, there are certain things organizations can look for to make sure they land the talent they want. The article provides a list of 10 jobs expected to be in demand for 2021, in addition to the skills and experience needed to land them.
Data, information, systems, network, and cloud security professionals are in demand as businesses increasingly rely on data for everyday business operations. These IT professionals ensure that enterprise IT initiatives remain safe from potential threats inside and outside the organization. They are also tasked with keeping on top of industry compliance regulations and future security trends, and ensuring hardware, software, and networks remain secure. Cloud architects are also very much in demand. Cloud architects oversee the cloud computing strategy of a business and are responsible for deploying, managing, and supporting cloud applications. Cloud architects typically have a strong understanding of multiple operating systems in addition to networking, programming, and security skills. Businesses should look for individuals with a strong knowledge of cloud services such as Amazon Web Services, as well as experience with governance, automation, and vendor management.
According to a new Burning Glass report, IT jobs involving DevOps and artificial intelligence are the most in demand at this time. Employers are offering up sizable premiums for professionals who can automate IT operations or deliver AI and machine learning capabilities. The report looked at more than 1.7 million job openings within the United States, and grouped similar technology skills into associated skill areas and assessed both the projected growth of each skill area over the next five years, as well as difficulties filling job openings for these skills. Along with salary premiums, the study looked at the most disruptive job roles seen in information technology. The areas projected to grow the fastest include quantum computing, blockchain and the Internet of Things.
The top 10 most disruptive IT jobs on the horizon include those related to quantum computing, connected technologies, fintech, and AI and machine learning. Quantum computing, for example, has seen a 135% growth in new opportunities. This area requires skills related to building and utilizing quantum computers and their applications. Connected technologies jobs require skills related to the Internet of Things and connected physical tools, as well as the telecommunications infrastructure needed to enable them, such as 5G. Fintech requires skills related to technologies such as blockchain and others aimed at making financial transactions more efficient and secure. AI and machine learning requires skills related to developing and utilizing programs, tools, and solutions powered by algorithms and other technologies that automatically respond and improve based upon prior experience or data. IT automation requires skills related to automating and orchestrating digital processes and workflows.
The DevOps engineer role remains one of the hottest and hardest-to-fill positions in IT, and popular job boards show many open DevOps engineer positions, as well as similar titles or roles. DevOps engineer interviews come with important considerations for both interviewers and candidates. While job seekers should anticipate technical questions around tools and processes, the people part of the equation is just as important, if not more so. No one person can have the entire end-to-end expertise in every system and platform that the team builds and supports. Working as a team and having an open mind is critical, so DevOps engineer interview questions tend to reflect that fact.
First and final questions in an interview are especially important since psychology shows they will be the easiest to recall later. As a result, they can have a lasting impact on the perception of the interview for both sides. Asking about times when a candidate has exceeded expectations or has faced a challenging opportunity will show what abilities a person has, above and beyond mastering a role. The demand for IT workers who are able to change, be creative, flexible, and driven is one of the top must-have skills. DevOps is not about one concentrated skill or platform, so this question opens a wide door to learning how someone approaches a role and solves problems. As things still will be difficult in 2021 given our global situation with the pandemic, it is essential that the person organizations hire is empathetic and can adjust to different situations.
Why Gamers Should Be at the Top of Your Hiring List
Built In, January 7
Since managing remote workers is complex, building the right team is a foundational piece of making remote work successful. That means considering not just the talent you need now, but also the skills your business may need as it grows. Hard skills, like proficiency with cloud-based tools, are important. However, as the distance between your customer and team increases, other skills like digital communication, having a product manager mentality, and setting and working toward goals independently are especially needed. As a result, organizations are increasingly finding that gamers tend to be excellent remote workers because of their digital skills.
Gamers have been masters of communication platforms since the early days of the Internet. Jumping between applications, styles of communication, and audiences is a skill modern workforces need to have, especially with more customer interactions occurring on social media. But digital communication skills do not only apply to potential customers. The same attributes of great communication as part of an in-game team translate to better communication from business units across departments. From puzzle games to role-playing and resource management games, give a gamer enough time and they will solve the problem in front of them. The ability to approach problems from different angles and employ new tools to get the job done is a critical trait that business leaders should be looking for as they shift their strategies to reach new customers. The emphasis is on solving the problem and either using existing tools in new ways or developing the tools needed to do it. This skill can help not only solve problems quickly, but it may also help a team identify product or UX challenges that can improve the entire experience of the platform.
Digital Careers Ahead: AI Instructors, Remote Work Heads, Digital Marketers
Forbes, December 22
Digital, AI and machine learning skills have already become a must for information technology professionals and data scientists. However, it is going to be just as important for non-tech business professionals to at least understand the power of digital and AI technologies. With it will come re-designed and re-oriented job roles, such as AI instructors who can train machine-learning systems. The impact of digital and AI may even be more profound on business professionals than it is on their technology counterparts. The primary changes in technical roles include the evolution of data engineer into cloud engineer, data scientists into full-stack developers, and product managers into digital product managers.
In the future, more companies will require heads of remote work, not necessarily as standalone roles, but added to existing management roles. It is also likely these leaders will be remote workers themselves. They have already been working remotely full-time for many years and have a unique perspective and insights into what it takes to make remote working successful. Companies will also need people who can delve deep and understand the productivity implications of hybrid work culture. This is an area that is not yet well understood. As companies yo-yo back and forth between fully remote and hybrid working models, there may be greater demand for something called industrial psychologists. As the title suggests, this is a role that applies psychological principles to the workplace. A person with this title would explore what motivates employees to do great work, how training can bring out leadership qualities in employees, how to cultivate alignment with cultural values and even becomes part of the candidate screening process. Related to this is will be professionals adept in the areas of organizational development and learning.
How to Become a Machine Learning Engineer
IT Pro, December 23
As companies adopt artificial intelligence (AI) technologies and systems, demand for machine learning engineers is soaring. Many career opportunities exist today, and there will be more need for people with machine learning training and experience to fill future roles. Machine learning engineers must know computer science, mathematics, statistics, data science, deep learning, and problem solving. They must also commit to learning several programming languages and have the patience to work with complex data sets and algorithms. There are many available resources online for people who want to become machine learning engineers, but the volume of information can make it difficult to absorb, making it a challenge to decide which career path to follow.
The average pay for machine learning engineers in 2020 was $147,134 per year. Job postings for machine learning engineers have grown by 344% from 2015 to 2018. Machine learning engineers typically require an advanced degree in computer science, software engineering, or a related field for the best career prospects. Most job advertisements in fields involving AI or machine learning are for machine learning engineers. The duties of a machine learning engineer are similar to those of a data scientist. They work with large amounts of information, need to perform data management, and do complex modeling on dynamic data sets. They also design self-running software to automate predictive models, which use their previous results to improve their accuracy in performing future operations. As the title implies, machine learning engineers work with machine learning, which uses algorithms to analyze data and improve predictive accuracy without human intervention. Machine learning also ties to AI and deep learning, which involve artificial neural networks that use deep data sets to think and solve complex problems.
Top Job Seeking Tips for Software Developers in a Competitive Remote World
BOSS Magazine, January 8
The remote work trend is here to stay, and businesses across the country have been forced to adopt remote work models quickly. While this means developers have plenty more options when it comes to job seeking, it also means that competition has become more intense than ever. True, developers are needed in every industry, but as this career space thrives, so too does the struggle for the search. With that in mind, recruiters and hiring managers have assembled a few important job-seeking tips for software developers looking to thrive in a remote world.
As a developer, you should understand that programming is a rapidly evolving industry. As such, you should adopt this mindset. Every day, different languages and tools are adopted in the tech world, and it is your job to pick and choose which you want to learn. From managing a container registry to learning cloud platforms, there are several skills essential to your career as a software developer. Many developers hone in on a specific language and live and breathe the tools that complement it. And while it is true you should specialize in a certain area, the last thing you want to do is pigeonhole yourself into a box. Today, companies want innovative developers that can think outside the box and understand modern technology. Anytime you apply to a software development position, expect your expertise to be tested. How your employer tests you depends on the role in question. They might test your general knowledge of development skills, your creative capabilities, or require you to write code.
Which Technology Jobs Will Require AI and Machine Learning Skills?
Dice Insights, January 8
Artificial intelligence and machine learning seem poised to dominate the future. Companies everywhere are pouring resources into making their apps and services smarter. But which technology jobs will actually require AI skills? Although artificial intelligence skills are very much in demand among software developers and engineers, data science is clearly the profession where AI is most in vogue. Indeed, there is a lot of overlap between AI and data science. Both disciplines involve collecting, wrangling, cleaning, and analyzing massive amounts of data. Whereas a data scientist will analyze data for insights that they present to the broader organization, artificial intelligence and machine learning experts will use those datasets to train AI platforms to become smarter.
Given the intersection of artificial intelligence and data science, many machine learning and AI experts become data scientists, and vice versa. That relationship will likely only deepen in the years ahead. Burning Glass suggests that machine learning is a defining skill among data scientists, necessary for day-to-day tasks. So, if you are aiming for a job as a data scientist, having extensive knowledge of artificial intelligence and machine-learning tools and platforms can give you a crucial advantage in a crowded market. Many other technologist roles will see the need for artificial intelligence skills increase in the years ahead. If you are involved in software development, for instance, learning AI skills now will prepare you for a future in which AI tools and platforms are a prevalent element in many tech stacks.
Project Managers Should Not Trust Their Programmers
Blog@CACM, January 11
Within any organization, there will exist a certain amount of tension between project managers and programmers. That is especially the case if your programmers are working remotely, or have been hired as part of a new outsourcing initiative. After all, there always exists the risk that the programming team will decide to jump ship, leaving you holding the bag. The departing team will have all the technical skill, documentation, and understanding of the software, while project managers may not understand the code. This scenario is common enough that it requires organizations to re-think how much they should trust their programmers.
Companies start by trusting their programmers and often think of them as partners. After all, they have all the technical skills you need, and are able to code and design world-class software. There is a major problem, however. The software they develop is theirs, not yours. So, do not trust your programmers, at least not completely. You can have faith in their abilities, you can believe their milestones and feel confident in the eventual outcomes. But you should never fully trust them. Instead, hold your programmers accountable. And you start by not paying for everything up front. Unfortunately, if you do so, there is a risk that they will take the money and run. And that risk is even greater if you have outsourced work to a team in a foreign country.
Reboot the Computing-Research Publication Systems
Communications of the ACM, January 2021
In 2020, conferences were forced to virtualize due to COVID-19. It is now clear that conferences will continue to be virtual at least until the middle, if not the end, of 2021, and perhaps even beyond that. This has important consequences for the computing-research publication system, which is badly broken and is in need of a serious reboot. Today, computing-research conferences are clearly the preferred venue for archival publication. However, conferences were never designed to provide a venue for high-quality archival publication, since they lack the appropriate editorial process, whose essential element is iterative improvement.
In order to overcome a dysfunctional, antiquated publication system, it is time to end the debate about journals and conferences. It is time to design a new publication system. In order to do so, it will be necessary to collect system requirements, design the system, implement prototypes, experiment, and iterate. Technology opens new avenues, but it is important to be imaginative and not be bound by the dogmas of the dysfunctional past. If we have learned anything from COVID-19 it is that dealing with major societal challenges requires collective action. Professional societies must lead the way in creating a publication system that meets the needs of science, of scientists, and of society.
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