ACM CareerNews for Tuesday, May 18, 2021
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 firstname.lastname@example.org
Volume 17, Issue 10, May 18, 2021
A little over a year after the first COVID-19 lockdowns in the U.S., the IT industry has recovered the jobs lost in the aftermath and added new ones. Moreover, that growth looks likely to continue in 2021, with the IT industry resuming the annual growth seen before the pandemic. The latest figures from IT employment consultancy Janco Associates show 23,600 IT jobs were added in April, based on the U.S. Bureau of Labor Statistics (BLS) monthly reports. In contrast, the total for February and March combined was 9,100, a big decline from earlier BLS estimates of 15,900 for the period.
More than 100,000 IT jobs were lost during the depths of the pandemic in spring 2020, but two-thirds of those came back as the year progressed. Still, 2020 ended with 33,200 fewer IT jobs in the U.S. compared to 2019. So far in 2021, 39,500 IT jobs have been added, more than erasing the 2020 net losses. In some geographic markets, there are more job openings than qualified candidates to fill them, and that is pushing up salaries. The Janco figures are similar to those reported by the CompTIA industry trade association, which calculated that there were 16,600 new U.S. tech sector jobs in April, following a gain of 9,600 in March, 7,700 in February, and 19,500 in January. CompTIA calculates both technical and nontechnical positions at tech vendors, whereas Janco looks at IT positions, including software developers, in all industries.
Demand for tech talent is ramping up around the nation, and it is not just the most popular tech hubs that are seeing a surge of job postings. While tech job postings are on the rise in cities like Austin and Seattle, it is also the case that tech job postings are soaring in locations like Milwaukee, Wisconsin; Albany, New York; Des Moines, Iowa; and Oklahoma City, Oklahoma. Rising competition for tech talent is a trend with high stakes that transcend the tech industry itself, as small businesses around the nation could find themselves battling to retain employees with coveted tech skills. Experts say the rise of work-from-home arrangements could complicate the issue as well by making it easier to hire from more diverse geographic locations.
The first few months of 2021 show momentum building for tech jobs due to a combination of a strengthening economy and pent-up hiring demand. Most notably, a host of mid-market metro areas recorded a surge in tech openings in March. For example, Milwaukee, Wisconsin; Albany, New York; Boulder, Colorado; Des Moines, Iowa; and Oklahoma City, Oklahoma all posted at least a 44 percent jump in hiring for tech jobs between the fourth quarter of 2020 and the first quarter of 2021. In addition, the data shows tech job postings are soaring in established tech markets like Atlanta, Austin and Seattle. Research from HR consulting firm Robert Half also found hiring is particularly strong in Miami, Detroit and Dallas. Overall, tech employment is projected to grow 2.5 percent for the year nationally.
Whether you are looking for your first data science job or figuring out your next career move in the field, you should understand some of the important trends and factors that are shaping overall demand for data scientists. After all, it is not just the biggest Silicon Valley companies that are looking for data scientists. Salaries for data scientists range from $50,000 to more than $150,00, and companies want full-time data scientists as well as data engineers who will work on contract. In general, organizations are looking for job candidates with an undergraduate or graduate degree degree in computer science, as well as experience with data modeling tools. The best data scientists will be expected to translate their know-how into actionable insights and compelling stories for different stakeholders across the business.
At the outset of their job search, candidates should look for the right data science role for their skills and experiences. While data scientist is the most familiar role to many candidates, the job of data engineer might actually be easier to land. Behind every good data scientist there is often a team of very good data engineers. In most projects, more than 80 percent of the work involved is data engineering. On Dice, there are many more postings for data engineer jobs compared to data scientists, and this is a trend found on other job search sites as well. Companies are also looking for data architects, predictive modelers, data storytellers, business intelligence developers, and machine learning experts.
Can We Make Coding Interviews Better?
Tech Republic, May 11
In order to attract the best developers, companies should re-think the format and structure of their coding interviews. In many ways, it seems like the interview process for programmers is inherently geared against them. While recruiters do need to make sure they are finding the right candidates, they also need to make sure that the coding problems that developers encounter are actually representative of what they might expect to find on the job. Most programmers, for example, say that many coding interviews are not representative of anything they would have to do in their day-to-day job, and say it is an outdated means of assessing candidates that does not reflect their skill level or their ability to design larger systems.
One major issue is that technical interviews are not standardized, meaning they can vary significantly from company to company. This makes it almost impossible for candidates to prepare fully. As a result, their fate rests largely in the hands of whoever is carrying out the interview on that day. When there is so much variability, biases begin making their way into the process. Of course, there are completely legitimate reasons for passing on a candidate. For example, if a company uses a specific programming language, tool or development framework the candidate is not familiar with, they are unlikely to be taken on, no matter how technically competent they might be in other aspects of programming. Just keep in mind that focusing too much on specific tools also risks excluding promising candidates.If you get too tool-specific, you are eliminating people who could have easily picked up whatever tool you are working with.
Robots Will Not Take Jobs If CIOs Start Preparing the Workforce Now
CIO Dive, April 13
Analysts and technologists may have overstated the idea that automation will replace the human workforce in the future. While there is some need to prepare for emerging technology disruption, that process of disruption might actually be less abrupt and jarring than many imagine it to be. For example, when MIT launched its Future of Work task force in 2018 in response to the idea that robots are taking away jobs, it found the technology shaping the future of work actually moves very slowly. CIOs and other business leaders have time to prepare, if they start investing in skills and adaptations now. On the whole, emerging technologies are unfolding gradually with time for companies and workers to adapt.
Stories of emerging technologies overhauling industries exist, but cautionary tales of businesses warning it will not happen overnight have also emerged. This gives companies some time and opportunity to adjust their policies accordingly. The impact of technology on jobs today mostly stems from mature IT that was introduced decades ago, such as the internet and cloud computing. There is a huge difference between when the technology first comes out of the lab, and when it gets deployed at scale. With AI, for example, establishing human-machine collaboration takes a lot of research and experimentation, and that is probably why AI is taking its time being deployed at scale. The technology that does cause disruption mostly works at the task level, not at the occupation level. As a result, jobs hold steady in the wake of emerging technologies, even though the tasks comprising the position may change. Where technology does cause disruption, it happens disproportionately to certain groups, such as less educated workers.
Candidate Screening and Social Media: What You Need to Know
Dice Insights, May 11
When it comes to hiring new employees, organizations today can not overlook the social media activity of applicants. Until recently, companies relied on references and background checks; now, they rely on content posted to social media platforms like Facebook and Twitter. In a 2018 survey conducted by CareerBuilder, 70 percent of employers reported that they were using social media to screen candidates before hiring and more than half said they had found content that caused them not to hire a candidate. Disqualifying information, according to those surveyed, included everything from inappropriate photos to discriminatory comments or posts about flagrant drug and alcohol use. As social media use has continued to climb, employers are becoming increasingly aware of the impact an unsavory social media post could have on their business reputation or overall cybersecurity posture.
There are the obvious things most employers want to avoid in a new prospect, but you also want to be careful as an employer about not being too quick to disqualify someone based on social media activity alone. It is important to do some corroboration as part of your screening and analysis, such as by comparing various social media platforms of the candidate. Obviously, people can be swayed by what they read on Twitter or LinkedIn, but you can not base your hiring decisions solely on social media. You need to make sure that you are fully compliant in your hiring process. You should be aware of your bias if one candidate has more social media accounts or social media activity than another candidate. If you are using social media as part of the process for scoping out new hires and doing screening, it should be done in a fair and balanced way. Each platform has its own format and audience, so they can not all be judged as if they are equivalent.
How to Spot a Collaboration Superstar in Interviews
The Enterprisers Project, May 12
Job interviews can be an effective tool to find the right people for a successful collaborative team. With that in mind, there are several important questions that organizations can ask candidates regarding cross-team collaboration. For example, interviewers should ask at least one question about how the candidate provides critical feedback to other employees. This can offer great insights into not just how a candidate gives and receives feedback, but also how the candidate works and encourages projects along. By asking the right questions up-front, organizations can lay the basis for strong team communication later.
Asking interview questions about a team project that failed can be one way to find a potential collaboration superstar. Any interviewee should be ready to provide examples of previous successes and projects that inspired pride. With this question, you get the opportunity to discuss examples of personal resilience and overcoming challenges. Collaborative people have unique capabilities to overcome failures. For instance, they are often more patient than other people. As an interviewer, you need to observe that the candidate stays calm during a troubled process and focuses on analyzing and solving the problems. Collaborative people also know how to handle conflicts when they encounter them. They usually react fast and think about possible ways to mitigate the issues. Try to observe the role of the interviewee in overcoming the challenges they faced and how they did it. Explore what they learn from the failure and how they perhaps prevent it from recurring. You want to observe whether candidates are willing to take risks and try new things.
How to Quit Your Job in the Great Post-Pandemic Resignation Boom
Bloomberg Businessweek, May 10
As the pandemic finally shows signs of subsiding, the tech industry could see a wave of resignations starting as early as this summer. When there is uncertainty, people tend to stay put, so there are pent-up resignations that did not happen over the past year. Moreover, the number of resignations this time could be much higher than in previous years because so many people have embraced the work-from-home mindset and no longer want to return to the 9-to-5 office routine. Companies are currently figuring out how to maintain their cultures and employees, so many are offering multiple options for employees returning to work. Before resigning, then, you should fully understand the future plans of your company and how it plans to adopt flexible work arrangements.
If you are thinking about quitting your job this summer, give a lot of thought to the reasons. Make sure you fully understand the future plans of your company, and how it will respond to remote work offers or flexible work suggestions. For example, if everyone is ordered back to the office, and the top three performers say they are quitting, the organization may rethink its decision. If you are unsure about when to quit, consider going back to the office for at least a week or two. Think of it as a test of your hypothesis. Humans tend to be really bad at predicting how they will actually feel. Moreover, co-workers may be having the same thoughts and, in that case, it will be important to see if you and your co-workers are approaching the decision of a pandemic resignation in the same way.
The Artificial Intelligence Era: What Will the Future Look Like?
The CCC Blog, May 11
If you are considering a future career in artificial intelligence or machine learning, it is important to understand the key factors and variables that could impact how that future develops. With that in mind, the Bulletin of the Atomic Scientists recently held a virtual program called The Artificial Intelligence Era: What Will the Future Look Like? The conversation focused on the recent March 2021 report of the National Security Commission on Artificial Intelligence (NSCAI), which analyzed the potential benefits and harms of AI. The two-year study presents an integrated national strategy to reorganize the government, reorient the nation, and plan for the coming era of AI-accelerated competition, with a focus on AI systems for the defense sector.
Currently, many people misunderstand the capabilities of AI systems and that is impacting how they think of AI impacting their career decisions. While AI has achieved human-level parity in some areas and by some definitions, there are still major gaps in understanding by both those who use and create the technology. And, while these systems work for very specific use cases, we have yet to understand how to use AI more broadly to augment human decision-making in the open world. As a result, there is a pressing need to define ideas like fairness. When corporations and government agencies use AI systems, they should be transparent about what objectives those systems are attempting to optimize, work with multi-party stakeholders to develop these objectives, and then continually test these assumptions and objectives to ensure fairness.
The 10 Best Practices for Remote Software Engineering
Communications of the ACM, May 2021
When we think of developer productivity, we typically think of effectiveness in terms of time management, communication, and task completion. Although we are drawn to personal workflow or time management tools, and learning secrets to improving our productivity, ironically this quest for optimal productivity can sometimes take us off course and be a detriment to our productivity. The problem is that accomplishing tasks or having a filled up schedule does not necessarily equate to productivity. Creating a formulaic working strategy, as was common in the last century, does not either. Productivity is less a quality that can be easily measured, controlled or improved directly with tools, but instead is a human element that manifests from developer happiness.
A core ingredient in workplace happiness and productivity is working on projects or software that you care about. In fact, this has been experimentally shown: happier workers are more productive, and lower happiness associated with adverse life events is a detriment to productivity. Thus, you should enjoy the practices of software engineering enough to warrant having it a part of your daily life. If you are not sure if you are in the right role, then assess it based on the small tasks that it encompasses. You can break your day down into small events or tasks, and take a mental note about whether or not you enjoyed each one. For example, a software engineer might realize they enjoy working publicly on open source on GitHub, and writing documentation, but are not so keen on re-answering the same questions on a private user forum. Figuring this out would help the software engineer to push for projects and responsibilities that are better catered to their interests. If you cannot identify any items, or if all the items identified are considered negative experiences, then it is time to look more critically at your role. There is no list of best practices that you could reasonably follow to make you happy if you are not in the right line of work.
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