ACM CareerNews for Tuesday, April 9, 2019
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@example.com
Volume 15, Issue 7, April 9, 2019
Within the tech sector, innovation is continually creating new jobs to replace old ones, with many of these positions commanding salaries well into six-figure territory. Even better, many of the best emerging tech jobs are all about pursuing intriguing discoveries while using the latest versions of IT tools. Based on factors such as projected market growth, the availability of positions and average annual salary, the list of the seven hottest emerging tech jobs includes R&D test engineers for self-driving cars, machine learning experts and blockchain developers.
At the top of the list is the job title of embedded systems R&D test engineer, with an average annual salary of $238,000. These are the professionals who make products like self-driving cars. There are 46 companies working on these products now, including tech giants like Google, Intel and Amazon. Another hot emerging job is deep learning architect, with an average annual salary of $213,700. This position pays the most, given the talent required to code machines so that they can process information on their own. The field is expected to grow at a rate of nearly 42 percent through 2023. Similarly, the job of machine learning engineer, with an average annual salary of $213,000, also ranked very highly. Machine learning is about more than robots. In the immediate future, machine learning engineers will usher in new advancements to support communications, transportation and Internet of Things (IoT) development.
Artificial intelligence (AI) is starting to influence the way candidates carry out their job searches and the way organizations recruit new employees. According to a Korn Ferry Global survey, 63 percent of respondents said AI had altered the way recruiting happens in their organization. Not only do candidates have to get past human gatekeepers when they are searching for a new job, but they also have to pass the screening of artificial intelligence that continues to become more sophisticated. Recruiting and hiring new employees is an expensive endeavor for organizations, so they want to do all that is possible to find candidates who will make valuable long-term employees for a good return on their recruitment investment.
Just like in other industries, artificial intelligence has the potential to streamline the job search process and take over time-consuming tasks for humans. There are several ways artificial intelligence helps candidates and companies during a job search and throughout the recruiting and hiring process. Candidates can use artificial intelligence job-seeking tools to find open positions that match their particular skill-set and discover organizations with the culture they want. This alone can save candidates an incredible amount of effort in an already time-consuming activity. Similarly, AI can conduct candidate outreach much more efficiently for companies so they can find candidates actually suited for the role. When the CV screening process is automated, it is much more efficient, which is appreciated by candidates and human resources departments alike. Additionally, since recruiters will not get bogged down in the CV review process, they have more time to nurture relationships with candidates.
Data scientists remain in high demand, but those interested in pursuing a career in the field must have the right skill set to land a job with a top salary, according to a report from Indeed Prime. Demand for data science professionals continues to rise as more companies seek to collect and analyze data and draw business insights from that information. Data scientist job postings have increased by 256 percent since December 2013, and median base salaries have reached $130,000, according to Indeed data. As more companies adopt data-driven approaches, data scientists must keep their skills current based on what employers need. With that in mind, the article highlights the data science skills in highest demand, and how and where to develop them.
One key skill for data scientists to learn is machine learning, which is a subfield of artificial intelligence (AI) that involves computer systems using data and algorithms to teach themselves to make predictions without being programmed to do so. The field will be key for advancing technologies including self-driving cars and increasingly personalizing the customer experience in areas like retail. Machine learning combines data science, math, and software engineering, so it requires an extensive skill set to learn. Machine learning skills include computer science fundamentals, programming, probability and statistics, data modeling and evaluation, algorithms and libraries, and software engineering and system design. There are different resources to learn machine learning. For example, Kaggle has a community of data scientists and machine learning engineers who work together to publish datasets, build models, and compete to solve data science problems.
6 Essential Skills Cybersecurity Pros Need to Develop in 2019
Information Week, April 3
While cybersecurity professionals continue to be in high demand by organizations around the world, it is no time for security veterans to become complacent about their professional development. Those who want to truly future-proof their careers need to start honing new skills now to keep up with changes in the industry. New security automation platforms, new architectures, and complex hybrid cloud implementations require major shifts in security technical knowledge. Not only is security technology changing rapidly, but so are many of the fundamental roles held by cybersecurity professionals. Many emerging technologies and pervasive use of the Internet of Things are touching every aspect of business operating models, and software delivery is becoming more agile and embedded into lines of business.
In terms of which skills to learn, there is growing overlap between cybersecurity roles and data scientist roles. As organizations become more disciplined about using threat intelligence, threat modeling, and risk metrics to guide their security practices, data scientists are increasingly helping both enterprises and security vendors take a data-driven approach to security. In many instances, these are career data scientists who are learning security on the fly. In addition, security professionals who can bring deep domain expertise to the table and begin to hone data science skills concurrently would be setting themselves up with two of the hottest skill sets in all of IT.
Forget Silicon Valley, Gen Z Views India and China as the Next Tech Hubs
CNBC, March 26
Silicon Valley has long been the center of the global technology sector, but that status could be starting to shift as more young workers are setting their sights on fast-growing IT hubs in Asia. In a new study of 12,000 women developers across 100 countries, tech hiring site HackerRank found that Gen Z workers born after 1997 were less likely than their older counterparts to view Silicon Valley as the primary destination for future tech careers. Globally, members of Gen Z now view Shanghai as one of the leading tech hubs in the world. Meanwhile, respondents from Asia-Pacific were more likely to view Indian tech hub Bangalore, and not Silicon Valley, as the IT center of the future.
Based on responses from Millennials and members of Gen Z across all regions, Silicon Valley remained the number one choice as the global tech center from now until 2024. However, the study points to a longer-term shift in the global tech industry as high expenses cause Silicon Valley to lose its charm. The cost of living in Silicon Valley is skyrocketing at a rapid pace, causing talent and entrepreneurs to explore other cities and opportunities across the United States. That has spurred the emergence of new American tech hubs, including Austin, Boston and Seattle. Elsewhere, countries like China and India have been working hard to innovate attract more investment. As a result, India and China are experiencing their own tech entrepreneurial boom.
How to Become a Software Engineer
Innovation & Tech Today, March 22
Software engineer continues to rank among the most in-demand tech jobs, and that is creating even more opportunities for people to become part of this fast-growing industry. By some estimates, there could be as many as one million unfilled software developer and software engineering jobs within the next decade, further driving up demand within the tech industry. In fact, a recent Gartner survey shows talent shortage is now the top risk for companies, because of the digitalization of their industries and the inability to staff for it. The good news is that it is easier than ever before to get started with software engineering.
If you are looking to get started with coding, the Internet is filled with free resources that will guide you to learn the basics. You can start with HTML and CSS, using online tutorials that will guide you through the basics of it. YouTube and Massive Open Online Courses (known as MOOCs) also have a lot of free resources. After leveraging these free resources, take stock of your experience. If you still like it, it is time to get serious and consider the next step. Coding bootcamps are a way to get enough basics that could help you to have a much stronger understanding of software that can be used within a professional context and even get you an entry-level coding job. If you are serious about having a career in software engineering and have the skills to work for top companies like Facebook or LinkedIn, opt for a longer and more comprehensive coding school.
Soft Skills: 5 Ways to Tell if Yours Need Work
The Enterprisers Project, April 1
As the role of IT has evolved from back-office cost center to strategic business partner, it has shifted some of the emphasis away from technical skills to soft skills. Effective IT leaders today need to communicate with large teams, lead prioritization efforts, hire outside the box, continuously network, and actively engage customers. Soft skills add credibility to the initiatives they drive, build trust, and ultimately help the business achieve its goals. The only problem is that soft skills are much harder to identify and measure than technical skills. In order to see if yours need work, answering a series of introspective questions can help.
In order to assess your soft skills, you need to consider how often you meet with people across the organization. The frequency with which you interact with people and business units outside of IT correlates with the strength of your communication skills. That is true for both CIOs and rising IT leaders. These experiences hone your ability to speak in a language that everyone understands, which builds influence. You need to win the hearts and minds of stakeholders so the technology succeeds in making the company more efficient and drives revenue. If you cannot drive adoption, you fail. Communication is key to achieving that.
Successful Managers Can Be Even More Successful If They Admit Failure
Inc.com, April 5
New research out of Harvard Business School suggests that high achievers can build connections and relationships in the workplace by admitting the failures they encountered on their path to success. In many ways, this approach is counter-intuitive, because top business leaders are expected to project an image of confidence, ambition and success. However, an aura of confidence does not always translate to connecting with people on a human level. Talking up your successes without humility tends to cause resentment among colleagues and subordinates. If you are highly successful, your achievements are obvious. It is more novel and inspiring for others to learn about your mistakes.
Acknowledging your own setbacks and shortcomings, rather than boasting about accomplishments, can be counterintuitive for high-achievers. However, this approach diminishes envy in others not so far down the path of success. Humility aims to move peers and workers toward admiration and away from resentment, thus increasing the chances of making successful leaders less like rock stars and more real and approachable. In one experiment, the HBS team found that people who read only about the professional and financial success of a person felt significantly more malicious envy than others who read a few extra lines describing the professional failures of that person.
How to Create a Great Team Culture
ACM Queue, April 3
Regardless of organization size, the best teams have one thing in common: a strong team culture. When a strong team culture is in place, people enjoy coming to work, the energy is electric, and the overall company often experiences long-term business success. In short, the team becomes greater than the sum of the individuals. There are a few key elements that can help to make this happen, such as the creation of a risk-taking environment where people feel safe to move outside their comfort zone. The team should also align around common goals and values, with a clear path forward. Team culture is one part of the job that great leaders never ignore.
The responsibility of a leader is to set the culture for the team. One way to do this is to lead by example. You have surely been in the situation where you have seen your manager staying late at the office, and as a result, you might have stayed just a little longer. Every day, people are looking for signals in their environment about what is the norm. As a leader, it is part of your job to set the example for those around you. You want to create a culture where people are engaged, cooperative, and excited. To do this, you need to be deliberate in your actions. For example, if you want to create a culture of psychological safety, where people can speak up and take risks, it is important that you do not accept or participate in negativity.
Will We All Be Wearing Wearables?
Blog @ CACM, April 2
In order for wearable devices to reach mainstream consumer adoption, academics and practitioners within the computer science field must address several challenges in the way they are used today. First and most importantly, CS professionals need to think about an expanded set of possible use cases for these devices beyond just healthcare and fitness. In addition, they need to address issues like interoperability, battery lifetime and their reliance on companion mobile apps in order to work properly. As the article points out, the way we think about wearable devices from a computing perspective has potentially important implications for the rate at which these devices will achieve mainstream consumer adoption.
In the same way that the transition from the desktop world to the mobile world represented one giant step forward in computing evolution, a similar transition needs to take place for wearable devices. If we constantly have our heads down, checking our mobile devices for information from our wearable devices, that is simply not a long-term solution. Wearable devices must be liberated from their tethering to mobile devices. The current state is that most apps on the wearable rely on a companion app on a mobile device. This is cumbersome because it requires having two or more devices in close proximity. In addition, the battery lifetime of the wearable devices must improve markedly in order to give greater range of motion.
Copyright 2019, ACM, Inc.