ACM CareerNews for Tuesday, September 3, 2024

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 20, Issue 17, September 3, 2024

These Are the Skills You Need to Get Hired in Tech
Computerworld, August 1

As the tech market shifts from massive hiring by enterprises to small-and-medium sized businesses adding new talent, the skills needed to attract the attention of employers are also changing. For example, the adoption of artificial intelligence (AI) has exploded, shifting what companies seek from more traditional roles to skills involving data, analytics, and machine learning. While tech hiring is not as robust as it used to be a few years ago, software developers and IT generalists are still the most in-demand roles in the U.S. today.

The IT industry is shifting from a candidate-driven market to one where multiple factors are at play. On one hand, major tech companies have announced significant layoffs due to over-hiring during the pandemic. On the other, small-to-medium businesses are finally getting a shot at closing skills gaps. That can prove advantageous for tech workers who might otherwise be locked into a corporate pay scale and roles that typically do not change quickly. Working for large companies that offer salaries or compensation packages higher than the average small or mid-sized business limits your options. You end up confined to the circle of a few tech giants to maintain the desired salary range. Both data and studies have shown organizations are dropping the traditional four-year college degree from job postings, opting instead for technical hard and soft skills or specific personality traits. By eliminating unnecessary and outdated degree requirements, employers open themselves up to a larger talent pool of would-be hires with skills learned through on-the-job training, boot camps, and certificate programs.

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How to Accelerate Your Data Science Career and Stand Out In the Industry
Dataconomy.com, August 23

With businesses and organizations increasingly relying on data-driven decisions, the demand for skilled data scientists continues to soar. However, standing out in this competitive field requires more than technical expertise. To truly accelerate your data science career, it is essential not only to refine your analytical skills but also to cultivate a unique personal brand. The key to standing out in the data science field is being able to combine core data science skills with hands-on experience gained from real-world projects.

According to the U.S. Bureau of Labor Statistics, data scientist employment growth is expected to be 35% from 2022 to 2032. It is expected that around 17,700 vacancies for data scientists will be released every year in the next decade. It is much higher than the average profession. Hence, it is crucial to master core data science skills for anyone looking to excel in this field. Proficiency in programming languages is essential, as these tools are the backbone of data analysis and modeling. Additionally, a solid grasp of statistics enables data scientists to make sense of complex data sets and draw meaningful conclusions. Data wrangling skills, which involve cleaning and preparing data for analysis, are also vital to ensure the accuracy and reliability of results. Beyond these technical abilities, understanding machine learning algorithms, data visualization techniques, and database management systems strengthens the capability to tackle real-world data challenges effectively.

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What Are the Most In-Demand Skills in Tech Right Now?
Silicon Republic, August 24

Skills in areas such as AI, machine learning, and natural language processing are at the top of the list for hiring managers. In addition, data science, data analysis, and data visualization continue to be in high demand. Cybersecurity, cloud and DevOps skills are highly valued as well. As new technologies emerge, companies are constantly evolving and thinking of new ways of leveraging these skills in order to adapt and stay ahead. In order to get hired, it is important to keep one step ahead of what these organizations are looking for.

AI and machine learning are fast becoming indispensable skills. Data analytics enables professionals to interpret vast amounts of information, driving informed decision-making and strategic planning. Cloud computing is also essential, facilitating scalable, flexible and efficient solutions for diverse business needs. Equally important are soft skills, which enable professionals to apply their technical knowledge effectively. Problem-solving skills are vital for navigating the complex challenges that arise in tech projects. Adaptability ensures that professionals can keep pace with rapid technological advancements and shifting client requirements.Going forward, digital skills will be crucial for every role across every sector.

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The AI Job Interviewer Will See You Now
Rest of World, July 24

The first step in the job application process could soon be a face-to-face interview with an AI avatar. These human-looking and human-sounding avatars typically work from a list of pre-determined questions and use a large language model to generate authentic-sounding responses on the fly. The number of companies using AI interviews is still small, and the jobs affected are often large-scale roles where companies need to sift through thousands of applicants at once. But as companies scramble for ways to integrate AI into their business, these experiences are likely to become commonplace.

The idea of using large language models to further automate the hiring process has already caught fire in the U.S. corporate world. A 2023 survey of 1,000 human-resources employees found that 10% of companies were already using AI in the hiring process, and another 30% planned to start the following year. The research firm Gartner listed natural-language chatbots as one of the key innovations for the recruiting industry, designating the technology as experimental but promising. The practice now appears to be catching on in China and India. In fact, one Chinese AI recruitment system provider performs hundreds of thousands of automated interviews each year, and lists multinationals among its clients. There are a variety of ways to automate the hiring process. The first step is simply to standardize the list of questions asked in the initial interview, a measure often adopted as an effort to fight cultural biases. Once the questions are standardized, there is only minimal benefit to human presence. Companies often transition from in-person interviews to remote Zoom calls, then to a pre-recorded video of a human, and finally to a fully computer-generated avatar.

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How Resumes Have Shifted Over the Past 5 Years
Fast Company, August 21

The job market has evolved, and so has the art of resume writing. Over the past five years, the combination of new technology, the pandemic, and market trends have had a dynamic impact on the workplace. And, in turn, that has changed the way that job candidates are attempting to attract the attention of hiring managers with their resumes. To help better understand the shifts that have taken place in resume writing, LiveCareer extracted data from 50,000 resumes from its internal database and compared resumes from 2018 with resumes from 2023.

In 2018, a typical resume created via LiveCareer was about 312 words. In practice, this means that the majority of users prepared single-page documents. However, the landscape changed notably in 2023. Resumes turned toward greater detail, with the average length surging to 503 words, equivalent to almost two pages. The evolution of the length of resumes between 2018 and 2023 signifies a departure from the one-page norm. Recruiters wanted extensive narratives, and this is what they got. Contrary to popular belief, one-page resumes have long ceased to be the norm. Providing more comprehensive information about skills, experiences, and qualifications offers a nuanced picture of a professional journey, emphasizing the value they can bring to potential employers. A 2018 study showed that recruiters are 2.3 times as likely to prefer two-page resumes to one-page resumes.

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In the eyes of job seekers, not all hybrid work schedules offered by organizations are the same. Based on a new survey of knowledge workers and IT leaders, hybrid is still the most common workplace model both globally and in North America specifically. But of the six specific types of hybrid arrangements, two emerged as the most popular among global organizations: scheduled hybrid and flextime hybrid.

Scheduled hybrid means there are set days or times when employees must work either in the office or remotely, while flextime hybrid means employees choose the hours they work, but they must still come into the office for certain meetings or collaborative sessions. These are the two most popular hybrid options among knowledge workers. In the survey, flextime hybrid ranked the highest, with 25 percent of employees saying that if they were to change jobs, they would consider this model in a new employer versus 23 percent for scheduled hybrid. Knowing you are going to see your team when you come to the office can be crucial for hybrid work arrangements. Otherwise, it can be chaotic, and people could continue to regret the commute. The other, less popular types of hybrid environments included in the survey were schedules based on worker locations, roles, or outcomes. For instance, with outcome-based hybrid, workers are able to work remotely if they meet specific performance criteria or project deadlines.

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7 LinkedIn Mistakes That Are Holding You Back
Dice Insights, August 26

The social networking platform LinkedIn can be a powerful tool for connecting with colleagues and industry professionals, but only if you use it correctly. Unfortunately, too many job candidates make several basic mistakes when building their personal brand and showcasing their expertise to potential employers. For example, too many job seekers treat their LinkedIn profile just like an extension of their resume, limiting its upside potential.

If you view your LinkedIn profile the same way you view your resume, that is the first thing you should fix. A good LinkedIn profile, especially the summary or about section, should tell a story that highlights what is unique about you. In contrast to a resume, which focuses on the past, your LinkedIn content should be aspirational or forward-looking and specifically address the role and the audience you want to reach in a compelling way. In other words, LinkedIn is about social selling. It is important to capture the attention of people who view your profile page. To engage your audience, keep the language informal and straight to the point. Tell the reader where you are headed by using your desired job title. Then tell them why you are an expert in your niche or specialty by sharing insights and ideas based on your knowledge, abilities and observations.

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How to Change Careers in 8 Steps
Built In, August 23

According to a recent survey, 58 percent of workers are trying to change careers. And many more people may rethink their careers and embrace continuous learning as technology reshapes the future of work. However, a career change is often complicated by uncertainty, and it can be difficult to determine where to start. Instead of fearing the unknown, you can gather information and build relationships that will help you turn your leap of faith into a well-calculated roadmap. This will lead to a career that better meets your needs.

If you are thinking about changing careers, first figure out what you want in the next stage of your career. Are you motivated by the potential for growth and a higher salary, or would you rather find a career with a better work-life balance? Do you yearn to make a difference in the world, or do you seek the job stability of an in-demand career field? Would you feel more at home in a new startup, a large corporation, or your own small business? Answering these questions is a good place to start. As you consider what is next for you, keep in mind that, if you are leaving a workplace environment you do not like, you may encounter some of the same dynamics in your next opportunity. Self-awareness is crucial when embarking on a career change, so you may want to meditate, write in a journal or talk with friends, family members, or a career coach about what is important to you and how that might manifest itself in the job market.

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The Myth of the Coder
Communications of the ACM, August 22

For nearly 75 years, the myth of the coder has persisted. According to this myth, there is a clear distinction between a programmer and a coder. But that simply does not appear to be the case. In fact, based on a review of the historical record, there appears to be a near absence of evidence for this distinction between coder and programmer. While the activities of coding and programming can be more or less clearly distinguished, the activities did not map onto different jobs, but rather were performed by the same person. It thus seems that the distinction between the coder and the programmer pertains not to the reality but to the mythology of early computing.

The distinction between coder and programmer originated in a famous 1947 report that outlined four hierarchical stages for planning and coding. At the top is the mathematical stage for the derivation of the algorithmic form of a mathematical problem. This stage was exclusively for the mathematician and had nothing to do with computing or with machines. After this, the coding process could begin, subdivided into three stages. The distinction between the stages would later provide the blueprint for the distinction between programming (planning or flowcharting) and coding (translating a flowchart into coded instructions for the machine). At the time, there was good reason for this distinction, as it was based on prior experience with the organization of labor for manual computation.

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Societal Impacts of Embodied AI
Blog@CACM, August 21

Embodied Artificial Intelligence (EAI) integrates AI into physical entities like robots, enabling autonomous perception, learning, and interaction with environments. Unlike earlier robotics, which focused on specific tasks, EAI fosters versatile robots capable of adapting to various situations. Going forward, it is important to explore the potential societal impacts of EAI, especially its ability to reshape social structures and daily life. It is also important to consider the impact that EAI might have on existing legal and regulatory frameworks, economic growth, quality of life, education, and overall productivity. The key question remains: Will EAI enhance societal well-being, or will it widen existing divides?

It is important to explore the societal impacts of Embodied Artificial Intelligence (EAI) to gain a better understanding of what adjustments need to be made going forward. Existing laws are often inadequate for managing EAI-related issues like data privacy, where AI systems continuously collect and analyze personal information. The autonomous nature of EAI complicates the establishment of clear regulations. Traditional frameworks struggle to assign liability for harm or errors caused by EAI systems, highlighting the need for new laws to ensure accountability and public safety. On the policy front, nations are engaged in a race for technological supremacy, implementing policies to build a robust EAI ecosystem. These efforts include investments in education and training programs, as well as incentives for startups to drive innovation.

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