ACM CareerNews for Tuesday, October 11, 2022
ACM CareerNews is intended as an objective career news digest for busy IT professionals. Views expressed are not necessarily those of ACM. To send comments, please write to [email protected]
Volume 18, Issue 19, October 11, 2022
12 Fastest Growing US Cities For IT Talent
CIO.com, September 28
Career opportunities for IT professionals are growing beyond the usual West Coast and East Coast cities that typically dominate IT hiring. The COVID-19 pandemic contributed to a boom in tech job postings in various cities across the country, as a large number of IT professionals relocated to new cities or states, and employers became more open to hiring remote workers. This was especially true for Silicon Valley, which saw a mass exodus of tech workers throughout the pandemic. While hiring remains strong in traditional tech hubs, such as San Francisco and New York, tech job postings have increased the most this year in cities such as Orlando, Miami, Detroit and Houston.
Within the United States, Orlando experienced the most significant increase in tech job postings, with 111% year-over-year growth. Typically seen as a city for retirees and tourists, Orlando is making a name for itself as a growing tech metropolis. The city is home to several colleges and universities, making it a hot spot for recruiting talent, and it is not too difficult to sell candidates on a move to Florida. Miami has also experienced a major surge in year-over-year growth for tech job postings. Much of this growth is attributed to the Miami mayor, who has encouraged technologists and tech companies to make the move to Miami. Companies in Miami are looking for software developers and engineers, project managers, network engineers and architects, IT project managers, and customer support specialists.
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Tech Recruiters Share the Ways They Find Candidates Fast on LinkedIn
Protocol, October 2
A significant amount of talent sourcing still takes place on LinkedIn, so many recruiters have found their own techniques to use the social media platform more efficiently. For example, when reaching out via LinkedIn, many recruiters have found that short and sweet is key. When sending a connection request, for example, it is best not to send a message of more than three sentences or 150 characters. It is also best not to ask for an appointment in the first message to a candidate. Specific, well-informed messages targeted to the candidate are also crucial to getting a good response rate.
When looking to find talent quickly, companies should focus on skills, not pedigree. Being able to contextualize skills from different work environments is key, particularly in a tight labor market. Organizations should have a clear understanding of how skills from one role can map to another role. This can be particularly useful for employers that do not have as much name recognition or as strong of a talent brand. It can also help a team source more diverse hires. Employers that are not yet a household name may want to consider skipping the first page of search results, or maybe even checking out the candidates on the last page. These candidates may not come from the companies you typically hire from, but it helps organizations think a little bit more broadly about who is capable of doing the job.
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3 Essential AI Roles to Hire Now
The Enterprisers Project, September 19
In almost every industry, artificial intelligence has become a mission-critical technology to address urgent business needs. In order to be successful, organizations need a solid team of technologists, data scientists, and product specialists as the foundation. Whether you are building a team from scratch or growing an existing AI team, there are several key components needed to bring together the right team. While every business is different and might have contrasting needs, several critical roles are at the core of a well-rounded, successful AI team.
Machine learning engineers are the key for moving from idea to production. Organizations need a machine learning (ML) engineer or researcher to build the models based on a given data set and the problem you are looking to solve. If it is a well-understood task, you can opt for an ML engineer. If it is a task no one has ever solved, then you will likely need an ML researcher. From there, the next crucial hire is an infrastructure engineer who creates and executes the supporting functions and backend infrastructure needed for the ML engineers to make AI models work. For example, when you want to build an AI model, you often need to scale your training and evaluation to run quickly. The infrastructure engineer makes it easier for ML engineers to iterate the loop of developing, training, and evaluating models. You also need engineers who can translate models from research into live production.
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Why a Failed Startup Might Be Good for Your Career After All
HBS Working Knowledge, October 3
Entrepreneurs coming off an initial startup failure often see their careers accelerate in their follow-on job. After exiting startups, these entrepreneurs obtain jobs about three years more senior than their peers, according to a new research study. The findings suggest that companies value the experience of entrepreneurs, who often have their hands in most aspects of the firm: operations, marketing, finance, communications, and product development. Clearly, general management skills win the day. The market values the experience they have and rewards them in terms of high prestige positions, even though they failed.
The research on startup ventures comes at a time when technologists are taking more risks, with people quitting their jobs in record numbers and many starting their own businesses. While some of those new businesses are bound to fail, as is typical, the findings provide some welcome encouragement. Entrepreneurs not only land on their feet after a failure, but actually move further up the career ladder. The research challenges previous studies finding that entrepreneurs who failed early in their careers often accepted jobs at a lower salary than their previous roles. In short, failure no longer carries with it a stigma. If you start something and fail, people are still going to want to hire you.
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5 Ways to Avoid a Technology Career Crisis
Dice Insights, September 29
Nearly 80 percent of tech professionals are looking for a new job, according to a new industry survey. Moreover, more than half said they had applied for a new job in the past month, while three-quarters had spoken with a recruiter. Nearly half had interviewed with another company. However, just keep in mind that job-hopping may not be the solution to a deeper career crisis. If you are feeling stuck on your current career path, there are plenty of other ways to head off this career crisis and keep moving forward.
Recognizing the root causes of a career crisis can help you develop proactive strategies to address them before you feel overwhelmed. When your role, industry, or work environment become misaligned with your personal and professional goals, it can make you feel demotivated, disheartened or lost. This leads some people to feel like they are experiencing a full-blown career crisis. There are various elements to this framework. Your role encompasses your day-to-day activities, responsibilities, projects and the overall style of your everyday work. Your industry relates to the ultimate purpose, mission or impact that your company delivers. Your environment refers to the company culture and how the physical or intangible environment looks and feels.
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6 Industries to Target for Landing a Programming Job in a Recession
Built In, September 30
Looking for a new software developer job in 2022 might seem daunting, especially given the news about layoffs at some companies, but if you know where to look, opportunities are endless. There are many industries that are growing quickly and hiring many software engineers. According to one recent report, the four fastest-growing industries globally are blockchain, advanced manufacturing and robotics, artificial intelligence (AI) and big data; and agricultural tech. Moreover, bioinformatics and cybersecurity are sub-industries that show huge growth potential.
The blockchain industry is expected to grow at a rate of 62% per year, from now until 2030. That means nearly 50% more job openings with each passing year, and with a predicted market size of $65 billion by 2030, that translates into a lot of jobs. The blockchain industry focuses on building software that incorporates blockchain technology, a method of ensuring trust between two parties on the internet. Subcategories are cryptocurrencies, NFTs, and decentralized applications. To get started in this field, the first step would be to begin taking courses online to learn the basics of programming blockchain applications, and then look for a software internship or job. There are a few universities that offer blockchain degree programs, but they are few and far between.
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How to Land a Six-Figure Job as a Beginner AI Engineer
Analytics Insight, September 26
Hiring of artificial intelligence specialists, including engineers, has increased 74% annually for the past four years. Despite this hiring surge, it can still be intimidating to apply for an AI engineer job, especially at the entry level. As artificial intelligence continues to seep into our daily lives, AI-related jobs will be among the fastest-growing jobs in the technological sector, creating additional career prospects for those with the right AI skills. AI engineering is a specialized field that has promising job growth and tends to pay well, especially if you are working at a major company in Silicon Valley.
In order to land a six-figure salary, AI engineers need to have insight into technological innovations that translate into state-of-the-art programs. To land such a job as a beginner AI engineer, you must have a good mix of technical and nontechnical AI engineer skills. AI engineers build different types of AI applications, such as contextual advertising based on sentiment analysis, visual identification or perception, and language translation. AI engineering is a field of research and practice that combines the principles of systems engineering and software engineering. AI engineers need to use software development techniques and practices, along with programming skills, in order to ensure that all AI-enabled machines operate smoothly regularly.
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Setting Career Goals When You Feel Overwhelmed
Harvard Business Review, September 30
The process of setting career goals is not always as rational or evidence-based as we would like to think. When new job obstacles seem to pop up around every corner and market conditions are always shifting, it can be difficult to think rationally about career goals. Research shows that to engage our motivational systems and direct our energy to the right actions, we need to have a clear sense of where we are, where we are going, and whether we are closing the gap between the two at the right rate. Without goals, we make bad choices and miss opportunities to act, so it is important to set career goals even when feeling overwhelmed.
To set goals that make sense and motivate ourselves and others in such uncertain times, we need to set them with a growth mindset. Having a growth mindset is a bit more nuanced than simply believing that improvement is possible. Your mindset is what you believe to be the larger meaning or purpose behind the work you do every day. A growth mindset is about believing that developing and making progress is the point of what you are doing. It is about getting better as opposed to just being good. And it is about engaging in specific growth mindset strategies and habits to help keep you focused on the potential for growth in everything you do. When you approach goal-setting through the lens of a growth mindset, you become more comfortable with uncertainty and more willing to entertain the idea of longer-term goals.
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Opportunities of Data Science Education
Blog@CACM, September 1
For the past two years, data science education has been gaining more and more attention as a new discipline. This makes sense, given the growing popularity of data science as a career path. The initial focus was on the challenges presented by data science education. However, now there is growing emphasis on the types of new and exciting opportunities that data science education presents. These include teaching STEM (science, technology, engineering, and mathematics) in a real-world context and teaching STEM using real-world data. It also involves bridging gender gaps in STEM education; teaching 21st century skills; interdisciplinary pedagogy; and professional development for teachers.
These new opportunities in data science education are largely based on and derived from the interdisciplinary nature of data science. The first opportunity is teaching STEM in a real-world context. Since data science attributes a great deal of importance to the application domain, that is, to a real-world context, it offers an opportunity to expand this perspective to the other STEM subjects. Although attempts have been made to implement this approach in different subject matters, such methods are not common since they are not simple for both teachers and learners to implement. In the context of data science education, however, as the application domain is integrated inherently, it is not only natural to teach mathematics, statistics, and computer science in a real-world context, but also essential and unavoidable.
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Toward Inclusive Design Methodologies for Technology
ACM Ubiquity, September 2022
Computer science curricula should aim at helping students appreciate the differences in the worldviews, skills, and abilities of technology users. In addition, computer science should teach students how to harness and embrace these differences in technology design. In a wide-ranging interview, an Egyptian computer scientist who earned her PhD in human-computer interaction (HCI) in 2012 from Virginia Tech in the United States discusses new computer science initiatives that she is launching in the Arab world. She also discusses her biggest concerns about the future of computing.
One major concern is how technology is envisioned, imagined, and designed. If it emerges predominantly from Western worldviews, there could be a problem if other parts of the world are mostly perceived as passive recipients and consumers of innovative Western technologies. In principle, there is nothing wrong with Western designs; it is the assumption that Western designs could and should work across the globe that is problematic. There could be a lack of fit of Western technology worldviews in non-Western cultures. For instance, most of the portable and wearable devices we use are designed for individual use. We take this for granted, but that design is influenced by Western worldviews that promote individualism and consumerism. In other places around the world, shared use of expensive artifacts among family members is the norm. Sharing applies to devices such as mobile phones and even personal fitness trackers.
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