ACM CareerNews for Tuesday, July 23, 2019

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Volume 15, Issue 14, July 23, 2019

Artificial Intelligence Jobs in 2019
Datamation, July 19

Artificial intelligence jobs are not a new phenomenon, but the AI job market is growing in complexity as new applications for AI are rapidly expanding. According to research firm IDC, AI is currently seeing an annual growth rate approaching 40 percent. Amid these changes, AI job titles have changed and expanded, while AI salaries are heading skyward. The rapid emergence of new AI titles reflects the fact that AI has become practical for mainstream use as the result of affordable cloud computing and storage costs. The growth of AI companies and the expansion of related technologies (such as machine learning) have expanded the types of AI job titles that jobseekers will encounter.

Currently, there are many different types of AI jobs and roles available, some of which merely add AI to an existing title, such as AI Developer. Others reflect different aspects of AI, such as Data Engineer, Algorithm Developer or Machine Learning Scientist. Jobseekers and career builders are wise not to take AI job titles at face value. For example, some companies require data scientist candidates to hold an advanced degree in Computer Science or Statistics, while other organizations may accept a BS or even no college degree and certain types of experience. Similarly, a senior title may require a graduate degree and more experience at some companies than others. Some of the most popular AI job titles currently include AI Developer, AI Engineer, Algorithm Developer and Data Scientist.

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Data scientist roles are evolving rapidly as organizations look for new ways to apply analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. Organizations can then use this information to develop data-driven solutions to difficult business challenges. At one time, data scientists came from a few narrow fields, such as mathematics and statistics. However, now data scientists have a wide range of technical competencies including coding languages, databases and machine learning.

Of all the top tech companies, it is no surprise that companies such as Amazon, Microsoft and IBM have the largest data scientist workforces. In general, data scientists want to work for companies that provide them with the right challenges, the right tools, the right level of empowerment, and the right training and development. When these four come together harmoniously, it provides the right space for data scientists to thrive and excel at their jobs in their companies. Currently, the United States contains more people with data science job titles than any other country, followed by India, the United Kingdom, France, Canada, Australia, Germany, Netherlands, Italy, Spain and China. Demand for data scientists far outweighs supply in developed markets such as Europe. The existence of a combination of established corporations and up-and-coming startups have given data scientists many great options to choose where they want to work.

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As the result of rising cybercrime activity and more stringent laws and regulatory standards, the demand for skilled and knowledgeable cybersecurity professionals in 2019 continues to rise. Not surprisingly, companies worldwide are upping their game to increase their defenses in this war against cybercriminals and hiring new staff to deal with security and compliance issues. This means that they need the best cybersecurity experts in place. Whether you are looking to get a start in the industry or seeking to revitalize your existing cyber security career, there are things you will need to know to be most successful in your job hunt.

To help yourself stand out from other cybersecurity professionals, create a compelling LinkedIn profile and a strong CV that highlights your achievements. Share details about complex projects or cyber security issues you helped your organization resolve. However, simply listing all of your accomplishments or skills is not enough on its own: you need to get out there to network and meet others in your field. Moving up in the technology field can come down to who you know. This is why networking is essential for every IT security professional. Thankfully, there are groups (both online and offline) that can help you connect with other cybersecurity and IT security professionals.

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Continuous Learning the Key to IT Skills Gap
Information Week, July 15

The economies of the future are being built around emerging technologies like AI and machine learning, but these jobs are increasingly lacking employees with the skills needed to support them. This problem was crystallized by a recent study, which surveyed 100 chief information officers across the UK and found that large majorities of them are already feeling the pinch of a skills gap in IT. In fact, more than three-quarters of them are concerned about whether their IT talent will require upskilling and whether their IT teams have the knowledge and expertise to keep up with the pace of digital change.

The challenge facing leaders today may be a shortage of skills that can keep pace with the rapidly changing landscape of IT and digital disruption. But that does not mean those workers lack the capability to learn new skills or improve on their current skill sets in order to keep up. Consider the skills that your current employees have that new recruits or contractors would not: intimate knowledge of your team structures, your internal processes, your products, your customers, what you are delivering to clients or end users, and the history of those product deliveries or user experiences. That kind of institutional knowledge is valuable, and something new hires will only pick up after a long period of time. By contrast, learning technical skills (a new programming language, new algorithms, new data-crunching tools, new applications for AI) can be picked up comparatively quickly.

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AI and Your Resume: How to Beat the Bots
The Enterprisers Project, July 16

It is only a matter of time before AI-enabled tools become even more prevalent and supplant current applicant tracking systems. Many larger companies are already using AI-candidate screening tools that focus on the whole candidate and not just a resume. As these tools become more mainstream and affordable, they will become more widely used. In addition, AI is infiltrating many processes related to recruiting and hiring. This includes screening candidate resumes in comparison to job descriptions and using AI-powered chatbots to streamline communications and schedule interviews. Organizations are recognizing that machines can be incredibly efficient in identifying the most qualified individuals in the candidate pool, thereby giving recruiters the chance to focus their time on more meaningful tasks and building relationships with best-fit candidates.

Candidates should highlight all their skills that are relevant to a particular role on their application or resume. Applicant tracking systems match keywords from job descriptions with resumes to find candidates that are the best fit for the role. Many AI tools also have semantic and synonym capabilities, so they can align similar language between job descriptions and resumes. Include any special projects, skill sets, and certifications, and the full name of relevant systems and software. It is important to be accurate, and define acronyms to avoid being filtered out of the pool. Moreover, do not try to game the system. Some candidates apply to several jobs at an organization with a slight change to their email address or name. Applicant tracking systems are designed to match similar profiles, so the technology will catch and flag this, potentially reflecting badly on the submitted resume and impacting the potential to be noticed by a recruiter. Recruiters have seen some job hunters overload their resumes with keywords they think will get them in the door or sneak some in a white font readable only by machine. While one may have the ability to trick an AI system to a certain degree, eventually a phone screening or live meeting with a hiring manager will bring to light that the applicant may not be as qualified as they claim.

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Want to Improve Your IT Career? Train Yourself, July 18

If you are interested in moving into a more senior role within the field of IT security, then additional training is practically mandatory in the long run. And if you are interested in moving on to an IT role somewhere else, then having at least something in the way of security certifications can help make that happen, too. But knowing that you want some additional security training and knowing which specific training you need to take are two different things. As you might expect, there are thousands of training choices available, some of which are definitely more useful than others. Making the choice more complicated is the emergence of very narrow specialties, which often forces IT jobseekers to commit to a certain programming language, framework or platform.

Before you even start thinking about which side of security you want to be on, it is important to get the basics right. Experts, for example, recommend a more generalist training route via the Certified Information Systems Security Professional [or CISSP] and studying the common body of knowledge (CBK). By studying the CBK, you will get a broad-based approach to cybersecurity capacity building while getting a better understanding of the tenets of confidentiality, integrity and availability. The CISSP certification is probably the best-known professional credential in security but it is not the only one that counts. For example, the Global Information Assurance Certification (GIAC) is also highly respected. The GIAC certification is considered by many to be equivalent to the CISSP certification. While there are likely a few IT pros who already have most of the knowledge required for the CISSP or GIAC certification, most people will need to take some training classes before they can pass the certification exams.

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How to Evaluate Company Culture During a Job Interview
Tech Republic, July 11

The majority of employees are more interested in the mission and culture of an organization, rather than salary and perks, according to a recent Glassdoor survey. In fact, 77 percent said they would consider the culture of a company before applying for a job there, and 56 percent said company culture is more important than salary when it comes to job satisfaction. Thus, having a compelling mission, culture and values are critical when it comes to attracting and retaining top talent in a competitive job market. Globally, it is clear that job seekers are seeking more meaningful workplace experiences. Job seekers want to be paid fairly but they too want to work for a company whose values align with their own and whose mission they can fully get behind.

Younger employees particularly value company culture, Glassdoor found. For example, 65% of U.S. millennials said they place culture over salary, compared to 52% of people over age 45. Culture impacts whether or not potential job candidates even apply to a given organization, the report found: 77% of adults consider company culture before applying for a job, and 73% said they would not apply to a company unless its values aligned with their own. This highlights the need for employers to clearly define and communicate their values with top talent. Company culture is also key for retaining employees, according to the report. Nearly two in three employees (65%) said their corporate culture is one of the main reasons they stay in their job. And 71% said that if their current corporate culture began to deteriorate, they would begin looking for jobs elsewhere.

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Boost Your Skills with New Online Technology Courses
Dice Insights, July 11

According to the latest salary survey from Dice, 71 percent of tech professionals say that training and education are important to their career development. However, only 40 percent currently have access to company-paid programs. As a result, many IT workers are looking for the most economical way to learn the skills they need without relying on their employers to provide the training. Fortunately, IT workers can bridge the knowledge gap by taking advantage of free online courses. Completing one or more of the latest training and development programs can help you acquire the skills to move into a hot specialty or high-paying job.

If your goal is to earn more money, consider becoming a mobile app developer. Mobile app developer ranked as the tenth-highest paying job for tech pros in the Dice Salary Report, with an average annual salary of $105,202 (a 7.6 percent increase from 2017). There is always a need for tech professionals who can build apps for iOS and Android. Moreover, acquiring Big Data skills can boost the careers and marketability of anyone in the current IT workforce. In terms of online courses available, Coursera provides a collection of essential skills that covers basics such as business case development, project planning, and sentiment analysis. The University of Michigan and Johns Hopkins University also offer well-regarded data science courses.

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What Help Should We Provide to Students Learning to Program?
Blog @ CACM, July 14

Within the computer science community, there is increasing attention to the diverse kinds of support that educators can and should provide to students learning to program. In fact, at the recent Notional Machines and Programming Language Semantics in Education seminar, that topic of teaching students how to program better emerged as a central theme. Currently, teaching students to program is still too hard. Educators can make it less intimidating and easier to learn with more support. Direct instruction works and is much more efficient than discovery learning, in which students must struggle to figure things out on their own.

Scaffolding is an umbrella term for different kinds of supports that help a student with programming. A notional machine, which is a human facing, student-accessible explanation for how some aspect of the computational machine works, is one kind of scaffolding. One of the reasons why learning to program is so hard is that educators mostly expect students to want to learn to program. We should show code that does useful things. Over and over again, students and educators have suggested that a grounded, concrete, working piece of example code was one of the best kinds of supports that can be provided to students. Humans are wired to learn from examples. Just telling students to go struggle with another problem is worse than useless and does not advance the learning process.

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Lazy Developers Are the Best Developers
Blog @ CACM, July 15

It might sound counter-intuitive, but the concept of hard work can be a bit problematic for software developers, because it often means going well above and beyond the original scope of the project. This is especially true when it comes to understanding legacy code. When you deal with legacy code, you often find yourself having to engage in so-called deep thinking. You are expected to understand large problem scopes before you even begin trying to fix the small bugs. The solution to this problem might be focusing on only doing what you are paid to do, and nothing more. In short, lazy developers might just be the best developers.

In general, clients want to keep costs low and if they can, they will pass costs onto outside companies. That is why some developers only do what they are paid to do. They will not go out of their way to improve a project or fix code unless they are getting paid for it. And when they find themselves with a task in front of them and they do not understand how to solve it, they usually do not blame themselves. This is especially true if the problem has something to do with legacy code. Developers are not paid to understand legacy code. They are paid to add a feature, solve a bug, or create new code entirely. Becoming experts in the legacy code of a project would be outside the scope of work. A project should not expect you to be intelligent or tech-savvy, as far as the legacy code is concerned. Instead, you need to focus on closing tickets. It is not your fault if the code is a complete mess, or the bug is serious, or you cannot estimate how much time it will take to understand the legacy code, let alone how to fix the bug.

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