ACM CareerNews for Tuesday, October 25, 2022

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Volume 18, Issue 20, October 25, 2022


The Best States in the US For Tech Jobs
Computerworld, October 20

According to data compiled from U.S. Bureau of Labor Statistics (BLS) monthly employment reports, the top states in the U.S. for tech jobs include California (35,947 tech job openings); Texas (27,284 openings); New York (16,142); Virginia (15,280); and Florida (14,015). Illinois was a close sixth, with 13,714 tech job postings. While those states all reported fewer openings in September than August, each still reported near record levels of tech jobs.

The top metropolitan areas for tech positions include: New York City (19,933 jobs); Washington DC (16,985 jobs); Dallas (12,279 jobs); Chicago (10,941 jobs); and Los Angeles (10,848 jobs). With the exception of Atlanta, the top 10 metro areas for tech postings also lost jobs over the past two months. New York City, for example saw nearly 3,000 fewer jobs in September than August. Dallas also saw its job number drop by more than 2,000. Overall, companies added 25,500 technology workers across the U.S. in September, according to the latest data from the BLS. The unemployment rate for technology occupations in September was 2.1%, down slightly from 2.3% in August. But that unemployment remains significantly lower than the national unemployment rate for all occupations, which is 3.5%.

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Developer Jobs: Nearly a Third of Top Tech Roles Remain Empty
ZDNet, October 20

Nearly one-third of key software roles are going unfilled as a result of hiring pressures and market shortages, according to a workforce study of more than 3,400 senior technology professionals. The study found that 30% of companies struggled to hire software engineers, data scientists and DevOps professionals in the third quarter of 2022. Despite this, nearly half (49%) of respondents said their company hired several people for their tech teams during the period. This contrast suggests that, even with aggressive hiring, employers are struggling to meet the heightened demand for skilled software professionals.

The survey also found that approximately one-fifth (21%) of companies had laid off employees on their tech teams during the third quarter of 2022. In some cases, companies were streamlining their tech teams, while recognizing the importance of still hiring for those pivotal roles. Earlier this year, a survey reported that tech recruiters anticipated hiring would be their biggest challenge of 2022, with full-stack engineers, software architects and machine-learning specialists proving particularly scarce. Despite news of prominent tech companies announcing hiring freezes and slowdowns, companies are still reporting a need for developers, and studies suggest that there might not be enough talent to go around. For now, skilled tech workers seem to be safe from growing economic concerns affecting other industries and professions.

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Tech Jobs See Remote Work Declines
Dice Insights, October 18

The remote work revolution may be losing momentum. Many technologists started working from their home offices over the past few years, but now a sizable percentage of managers and executives want them back in the office. At larger companies (those with more than 500 employees), approximately 67 percent of managers now want employees back in the office five days per week, according to a recent survey. Many managers seem to think employees are more productive when they know they are being watched by upper management.

The monthly jobs report from CompTIA suggests that remote work opportunities are declining yet again for key technology professional positions such as software developer and IT support specialist. However, the total number of remote work jobs remains significant. Despite the trends suggested by this data, managers who want technology professionals back in the office might have a struggle on their hands. The latest edition of the Stack Overflow annual Developer Salary examined data from 58,958 respondents worldwide and found that around 42 percent were already fully remote; another 42 percent were hybrid; and 14 percent were fully in-office. Smaller organizations (those with less than 20 employees) are most likely to be in-person, while the largest organizations, with 10,000 employees or more, are most likely to be hybrid.

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The Cybersecurity Hiring Spree Requires a Recruiting Rethink
Dark Reading, October 17

Shortages of trained cybersecurity professionals are forcing the industry to come up with some creative recruiting and training solutions. However, this might be harder than it sounds since automation is increasingly performing the tedious entry-level tasks that early-career cybersecurity specialists once did, making it harder for workers to gain early experience. The result is demand for job openings requiring some previous cybersecurity experience over the past year grew 2.4 times faster than the rate of the rest of the economy, while only 65 cybersecurity professionals are in the workforce for every 100 available jobs.

Overall, there were 769,736 cybersecurity job openings listed over the 12-month period ended September 2022. The data reaffirms the critical importance of feeder roles and thinking more creatively about on-ramps and career pathways. Experts see this trend continuing. As a result, organizations should be committed to ensuring that cybersecurity professionals are prepared for the current and future challenges this will bring. Employers are increasingly searching for potential hires with cybersecurity skill sets across other specialized areas of the business including auditor, software developer, cloud architect, and tech support engineer.

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What Attracts Top Tech Talent?
Harvard Business Review, October 19

Companies are having a difficult time finding, hiring, and keeping the top technical talent they need to keep their businesses running and growing. Employers used to think that appropriate pay was enough, but that has changed. To attract and keep talented people, companies need to understand how worker priorities have shifted and be able to offer people what they are really looking for. To shed light on why top tech talent stay in a job or choose to move on, Bain surveyed more than 500 tech employees and 230 enterprise technology organizations globally.

The Bain survey highlighted the fact that workers make employment decisions on much more than compensation alone. It also highlighted there can be a striking difference between the factors that influence a decision to join a company and those that determine how long a tech employee stays there. Employers often worry that their people leave because they are not paid enough. And while it is true that talented people will change jobs for more money, it is not usually why they start looking. Dissatisfaction with their role may lead them to start looking, and once they do, they often find new jobs at higher salaries that help confirm their decision to move on. The top reason otherwise engaged employees decide to look for a new job is a lack of learning and growth opportunities.

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Employers Should Prioritize Retention Over Hiring Study Suggests
CIO Dive, September 23

Employers may be more concerned with finding new employees than retaining existing ones, to the potential detriment of their organizations, according to an MIT Technology Review report. While 62% of employers surveyed said they struggle with increased recruiting costs, only one-third said that high staff turnover is a problem. To improve staff retention rates, leaders need to develop new career paths for staff members. Robust learning programs, in addition to a culture of learning and development, may be a key retention tool for those organizations.

Employers contending with an unprecedented talent market and looming recession have begun labor hoarding. With these employees already aboard, the next step is to prepare them for new roles within the organization. As a result, organizations may find that creating a culture of learning and development is a necessary next step to keep workers on board. Other surveys have shown that workers are reshuffling where they work to find greater flexibility and opportunities for advancement. The big takeaway is that companies need to showcase paths of growth within a company to keep talent engaged.

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24 Mistakes That Make Hiring IT Talent Harder
CIO.com, October 18

Demand for tech workers remains high, with no signs of easing up. For example, there were 319,652 job postings for IT workers in August. The month before, there were 371,847. That kind of competition for talent puts pressure on CIOs and their recruitment teams to be strategic in hiring decisions. Quite simply, they cannot afford to make mistakes if they want to successfully fill open positions. With that in mind, the article reviews some of the most common hiring mistakes made by IT organizations.

One mistake that organizations make when hiring is dedicating too many resources to training when workers have no place to go. This creates a mismatch between existing training programs and projected staffing needs, a situation that can leave both managers and workers frustrated. Sometimes CIOs invest in training their people but do not have a clear next step for these people. Moreover, the CIOs may not have a good succession plan, so when those people move into the new positions, there is also nobody to backfill their old roles. Another mistake is failing to align IT hiring with business objectives. With IT now thoroughly intertwined with business processes, CIOs need to tightly couple hiring strategies with the roadmap of their organization. That requires a solid understanding of business objectives.

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The Future of Pay Transparency in Tech
Protocol, October 4

The new California pay transparency law promises to shake up compensation in the tech industry by requiring employers in the state to list pay scales in job ads and reveal pay information to both the state and to current employees. Since the new law applies to companies with as few as 15 employees, tech startups will also report pay data. Five or 10 years ago, it was not unusual for 50-person companies to be operating without a formal career ladder in place. That will change now, as nearly all companies will need to have formal compensation bands for different job functions and levels.

Because the new California law applies to companies with just 15 employees, even tiny startups will be required to define their pay bands in a more structured way. It can be difficult to have a band for every single job, because sometimes startups just have one person in a job. The hope, though, is that it nudges companies to be a little bit more thoughtful in defining what is the job, what is the relative seniority, and what would be reasonable pay relative to market-based pay. Companies may find other ways to differentiate pay in order to compete for the best talent. The law only requires companies to disclose base pay, not stock, bonuses, or benefits. This means bonuses and equity could become more important forms of compensation, which may shift the issue of unequal pay to other areas. Bonuses may prove to be even more important levers for attracting and retaining great employees.

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The Many Shapes of a Computer Science Career
Communications of the ACM, November 2022

When you launch a career in tech, it often means having to decide on a specific role or a specific job title. These roles are all clearly defined with their own sets of mostly non-overlapping skills to help companies hire the right talent. But that is not the way IT workers define themselves. Most have a variety of skills that do not all neatly fall into one box. They collect skills across multiple dimensions over a lifetime of different experiences. They might start with a basic job function or clear-cut job title, but over time, it becomes much more difficult to put all those skills and experiences into just a single category.

The key things computer scientists learn on the job include: how to break down problems into smaller chunks; how to think at the systems level; and how to develop a greater awareness of the workings of systems, whether they be software systems or systems of people. People are never boxes; they are puzzle pieces that can fit together in more than one way. Many people find that, when it comes to their career, it is better not to try to fit in a box. Embrace breadth and depth as they are not mutually exclusive. Learning how things fit together is a skill that can make you successful, no matter which puzzles you find yourself solving along the way.

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Up with Data Science
Blog@CACM, November 2022

From a historical perspective, machine learning has been considered part of artificial intelligence. It was taught mainly in computer science departments to scientists and engineers and the focus was placed on the mathematical and algorithmic aspects of machine learning, regardless of application domain. Thus, although machine learning deals also with statistics, which focuses on data and considers the application domain, until recently most machine learning activities took place in the context of computer science, where it began, and focused traditionally on algorithms. However, the focus now appears to be shifting to making machine learning part of data science, a new interdisciplinary field of research that focuses on extracting value from data while integrating knowledge and methods from computer science, mathematics and statistics.

Some educators now propose that organizations stop teaching machine learning to those whose core discipline is neither computer science nor mathematics and statistics. Instead, these populations should learn machine learning only in the context of data science, which highlights the relevance of the application domain in each stage of the data science lifecycle, and specifically in the modeling phase, in which machine learning plays an important role. If this suggestion is accepted, not only will the inter-disciplinary nature of data science be highlighted, but the realization the application domain cannot be neglected in data science problem-solving processes will be further illuminated. Instead of teaching machine learning, institutions should teach data science.

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