ACM CareerNews for Tuesday, April 7, 2020

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 16, Issue 7, April 7, 2020

What the Best Developers Do To Be Great At Their Jobs
DevOps.com, March 24

With software development employment in the U.S. expected to grow by 21% by 2028, the need for talented developers is only going to increase. Now more than ever, organizations will be looking for new ways to hire the best candidates possible. As a result, it will become increasingly important to demonstrate your skills and dedication to the profession. The gap between a good developer and a great one is bigger than you may think, and one that needs to be highlighted on any resume and throughout the entire hiring process.

The best software developers know how their skills fit into the big picture. While a good coder handles the responsibilities they have within their role, the best coders take the time to understand the foundations of how businesses work, including revenue, profit, bottlenecks and the strategies of departments other than their own. This might mean investing extra time into general business self-education or holding meetings with other departments. These coders recognize the importance of grasping how the business units of an organization come together to keep things running and exactly how they fit in. By having this comprehensive view, they can hold influence in areas outside their technical domain of expertise and clearly match the mission of the business to their own work.

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How Artificial Intelligence and Machine Learning Are Used in Hiring and Recruiting
ZDNet, April 1

While online job sites remain a major focus in talent acquisition, artificial intelligence (AI) and machine learning are transforming the recruiting and hiring landscape. The power of AI lies in its ability to process high volumes of data at fast speeds, improving efficiency and productivity for HR departments. Those features and benefits can be applied to the hiring process in a variety of new ways. For example, major companies across various industries use AI and machine learning to navigate through thousands of applications, organize interviews and conduct initial screenings.

Talent sourcing is one of the most prominent ways companies use AI and machine learning technology for recruitment. AI is very helpful in scraping social professional sites, academic information, and a variety of different sources to help pinpoint the talent that companies are looking for. As a result, AI has been a gold mine for recruiters as they are looking for talent in an increasingly hyper-competitive labor market. Thus far, automation in candidate engagement is the most mature application in recruiting. Primarily, this is because candidates have become much more like consumers than they were before. They expect transparency in the process and timely responsiveness to their questions. Before AI adoption, most recruiting functions were not set up to do that well. They are now using innovations like chat bots to communicate directly with candidates at different stages of the process in order to let them know where they are in the process and where they have to interview next.

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Digital transformation requires specialized IT skills that are challenging to find for many organizations, especially given the current IT skills gap. In order for enterprises to stay ahead of their competitors, they need to have a pulse on what the IT workforce looks like today as well as what their teams will need in five to ten years to prepare and retain talent. Given that IT recruiters are seeing a lot of demand driven by digital transformation initiatives, it is important to understand how broad, overarching trends like distributed workforces impact the overall hiring decision.

At this moment in the talent war, location should not be an obstacle for hiring. According to the Future Workforce Report, younger generation managers are 28 percent more likely than their Baby Boomer counterparts to include remote workers on their teams. Additionally, with the current attempts to contain the spread of the coronavirus, there are early signs that this pandemic could accelerate businesses adjusting to allow for distributed work. Teams that put the right infrastructure and processes in place to be remote will not only have a competitive advantage for talent, but they will also be set up for success when it comes to longer-term talent strategy. By not confining your business to a specific location, it opens the door to a larger and diverse talent pool, as well as unlocks more economic opportunities.

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IT Recruitment: Time to Take a Non-Traditional Path
Information Week, April 3

To fill open roles, tech companies will increasingly need to pursue non-traditional recruiting tactics. In 2020, IT leaders should adopt a three-fold approach to solving the problem: identify and train people working in other fields; reach out to talented individuals who have left the workforce; and look to untapped geographic regions for the next generation of talent. Beyond headcount, these avenues will open opportunities for greater diversity in the workplace, and an influx of fresh ideas as a result. Not only will these recruiting methods fill empty desks, they will address a long overdue issue: how the technology industry can better diversify its talent.

A variety of re-skilling and up-skilling programs have popped up in recent years to tap into workers who have college degrees or equivalent experience, but who might need additional training to work in tech. For example, there are apprenticeships for mid-career workers called midtermships. They are the adult version of internships and often lead to full-time positions at tech companies. Not only is this appealing for workers who want or need to transition into a new field, but it also brings the kind of outside perspective IT leaders are looking for to inspire creative ideas and new innovations.

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Five Strategies To Help You Navigate Career Transitions
Inside Higher Ed, April 6

Whatever type of career transition you may find yourself facing, there are five strategies to help you navigate any feelings of culture shock you may encounter along the way. Potential culture shock-inducing career transitions are as varied as they are numerous. They can be either academic or professional in nature. For example, in recent weeks, many IT workers and recent graduates have taken on the unexpected challenge of migrating to online learning and work environments in response to the global COVID-19 pandemic.

In order to mitigate culture shock from any mid-career transition, the first step is to build relationships in your new environment and ask questions. Making connections and building relationships with your new colleagues are great ways to help accelerate the process of adaptation and navigate the implicit attitudes, values and beliefs of your new professional environment. If you are part of a team, start by getting to know the people you will be working with closely. Both long-term veterans of the team and those who have recently transitioned into their role can offer valuable insights into spoken and unspoken organizational expectations. To broaden your professional network, consider asking your supervisor who they think you should meet outside of your immediate team, or inquire into potential opportunities for mentorship. Having colleagues whom you feel comfortable reaching out to can be especially helpful when the frustration stage strikes. Particularly in collaborative and team environments, those you work with will often have an incentive to help you succeed.

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Six Interview Tips For Hiring Managers
The Enterprisers Project, March 24

Throughout the interview process, IT managers need to put in the work necessary to identify great candidates. If they do not, they risk making decisions based on imperfect information or biased assumptions. Before every interview, imagine you are about to meet your next star programmer. If you were hiring someone who will be with your company for the next decade and become a foundation for your department, you would probably put extra time and effort into preparing for the interview. A 30-minute conversation is an imperfect vehicle for choosing a pivotal team member, but when you structure it well you can learn enough to help you make an informed decision.

Savvy recruiters realize that interviewing is a two-way street. Just as you are evaluating the candidate, he or she is also assessing you and the organization. If you are running late, distracted, or generally ill-prepared, why would they want to work with you? Moreover, hiring managers should try to avoid the stress interview as much as possible. The interviewing process is already inherently stressful, and the last thing any candidate needs is for an interviewer to amp the stress up to eleven. Candidates are meeting a group of strangers who are judging their fitness for the position. Interviewees reside in a constant state of unease, never knowing what question is coming next.

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How to Scale Up Your Startup Workforce Without Killing Its Culture
Tech World, March 30

The new mobile, work-from-home reality within the tech sector has the potential to reshape the hiring process for startups for years to come. Before the current coronavirus pandemic, the UK startup scene was booming, and companies were quickly outgrowing their office space as they added new staff at breakneck speed. Now, they must use lessons learned during this initial wave of growth to scale their businesses at a time when teams are much more distributed and employees are working remotely.

In order to build up the most diverse and impactful team possible, many recruiters focus on how they can leverage candidate networks and internal referral plans. In addition, they also attempt to be visible at the right conferences and events and leverage unpaid media exposure in order to get better company brand visibility. Another key to recruitment for high growth is to behave in a principled way. This means building diversity and inclusion into the process itself, as well as standardizing as much as possible across all candidates. The goal is to make sure that the experience is consistent for candidates. Regardless of whether they are selected for a role or not, they should leave with as good an impression as possible. It can be very difficult to manage the hiring challenges of scaling at pace, but people who are attracted to working at a startup are often pretty flexible and adaptable by nature.

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Machine Learning Engineer Interview Questions: What You Need to Know
Dice Insights, March 23

Machine learning is one of the most in-demand areas for tech employment at the moment, and hiring managers are continually coming up with new interview questions to help them spot the most talented prospects. Candidates who thrive in this hiring environment are generally skilled not only in computer science and programming, but also statistics, data science, deep learning, and problem solving. During the interview, machine learning engineers must be able to show that they would be able to work as part of a cohesive team that may have been put together on very short notice for deploying new technologies.

In terms of the most important machine learning skills, a lot of data engineering and machine learning roles involve working with different tech stacks, so it is hard to establish a hard and fast set of skills, as much depends on the company you are interviewing with. For example, if it is a cloud based-role, a machine learning engineer is going to want to have experience with AWS and Azure, and for languages alone, Python and R are the most important. Ideal machine learning candidates possess an analytical mind, as well as a passion for thinking about the world in terms of statistics. Recruiters would like to find someone who can connect the dots and has a statistical mind, someone who has a head for numbers and who is interested in that outside of work, rather than someone who just considers it their job.

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The Rise of the Data Engineer
Blog @ CACM, March 30

The introduction of artificial intelligence (AI) into products and services across all sectors is leading to a fundamental change in IT personnel decisions. This shift is changing the roles of certain engineers and creating an entirely newfound requirement that demands an entirely new engineering specialty. In short, AI will challenge the organizational structure of conventional front-end and back-end engineering roles, and create new engineering roles that recognize data as a critical cog in the development engine.

The second phase of organizational change at the core of AI development following the introduction of data scientist to the mix is the rise of the data engineer. This newly emerging class of engineer is tasked with building the data pipelines and the scaling mechanisms to leverage elastic computer resources for AI workloads. Their job is to supply the data scientists with the cloud-based or on-premise data and infrastructure so their algorithms can effectively access and run their experiments to build the ultimate model for deployment. Organizations that have recognized this need are now moving quickly to restructure their AI teams by introducing data engineers into the process. This adjustment gives them a clear advantage over the competition still struggling to force their data science teams to effectively function within their existing IT or R&D organizational structures.

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New Ways to Think About CS Education
Communications of the ACM, April 2020

The shortage of computer scientists is a worldwide problem, and despite many recent initiatives, it has proven difficult to create new pathways into computing. Educational institutions need to be leading the charge here, finding new and untapped resources for transitioning people into computer science. In addition, CS educators need to be more attuned than ever before to the ethical responsibilities of future CS professionals and the need to integrate ethics into the technology development lifecycle.

Some universities are tackling the CS shortage problem by opening up their computer science programs to people with degrees from other disciplines. This allows individuals without any computing background to complete a second degree in CS on an accelerated schedule. The goal of these educational institutions is attracting new audiences to CS, so a key underpinning of the admission process is that no prior knowledge of programming is assumed. In many cases, students can pace their coursework if they need to balance study with work or caregiver responsibilities. In order to retain students, it is often necessary to create a virtual environment that mirrors the on-campus experience. Software can help to replicate the active learning format used in campus classrooms, including small-group instruction and interactive sessions with instructors and teaching assistants. Students have the same advising, tutoring, and career services support they would receive on campus, and a mentoring program can pair entering students with experienced ones.

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