ACM CareerNews for Tuesday, January 5, 2021
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 17, Issue 1, January 5, 2021
The type of company you work for can have a huge influence on your salary and other kinds of compensation in 2021. In addition, your salary will likely increase if you jump to a management track or deepen your skills as a specialist. If you are driven by the prospect of outsized compensation, make a point of pursuing hot in-demand skills such as machine learning or AI that relatively few technologists have mastered. For highly skilled, in-demand roles such as data architect, cloud engineer, and DevOps engineer, the salary premium is often quite high. Best of all, your specialization within your chosen field will mean that you will have lots of job opportunities so long as you keep your skills up-to-date.
Basically, there are two ways to boost your salary: negotiating with your current company for a raise or moving to a new company. If you want your current company to give you a raise, your annual review is the best time to make that ask. Raises are often hard to obtain outside the standard review cycle. Sit down and explain to your manager how your current scope of work makes you more valuable than what you are currently being paid. If you can bring data that backs up your argument, do so. For instance, if you have created a new line of business or figured out how to save the company lots of money, you have substantial leverage in negotiations. During your annual performance review, your manager may proactively offer a raise that you feel is too low. If that is the case, you do not have to automatically accept it. Instead, you can take a chance on asking for more, especially if your scope of responsibilities has increased over the past year. In a similar fashion, if your manager proposes a raise in exchange for an expanded scope of work, you will need to analyze whether the extra dollars are worth the increase in your workload.
With the exploration, analysis, modeling, and generation of meaningful information from data a new business priority, organizations are prioritizing the hiring of data scientists. In order to analyze this data and generate ROI, these organizations need talented data scientists, data engineers, and AI engineers to turn that potential into real opportunities. Yet, there is a shortage of skilled resources. There are two types of talent deficits: data scientists, who can perform analytics and analytics consultants, who can understand and use data. The talent supply for these job titles is extremely scarce, and the demand is enormous.
While data science is an overreaching term, within its larger meaning, many other sub-roles are available. Roles like Data Scientist, Data Architect, Data Analyst, Business Analyst, BI Engineer, Database Administrator, and Data Analytics Manager are in high demand. When looking for a new job, just keep in mind that there is a big difference between doing academic and research work in universities and working on real-world projects for companies. In academia, you are typically training and testing your machine learning models on data sets that have been cleaned and preprocessed for educational and research purposes. Your input is data and output of precision and accuracy metrics. The focus in these ecosystems is to learn and to push the limits of science. But when it comes to real-world applications, tools that people will use in their everyday lives, different challenges come up. Data can be scarce, hard to gather, fragmented, or non-existent.
A growing number of companies are expanding their offerings of training and retraining options to individuals who want to pursue new opportunities in cloud and digital. That coincides with an overall global need to reskill large segments of the populace and workforce. Companies such as Amazon are now looking to bring cloud computing skills to people around the world for free. The plan is to expand current training programs as well as introduce new initiatives to meet this objective. The programs include foundational training to become cloud practitioners as well as more advanced paths such as machine learning.
Recruiters are now seeing a whole new set of individuals going into tech. That includes baristas, fitness trainers, and others who have a desire to learn and want to pivot their careers to technology, through the variety of means being made available to access the education. There is a huge cloud skills gap and organizations need to be intentional about how they are serving up that content in a way people want to consume it. Professionals in traditional IT roles have also looked to these courses to transition to cloud-based roles. Organizations across multiple industries migrating to the cloud continue to drive demand for solution architects, developers, DevOps roles, machine learning, and other specialties.
How AI is Helping Top Tech Talent Connect With the Best Opportunities
Fast Company, December 16
In the new hiring environment of remote work, AI is playing an important role in helping organizations hire top talent. As a result, focus is shifting to the impact of artificial intelligence on hiring practices. Organizations are becoming more sophisticated about measuring the value, impact, and importance of people. In turn, talent management experts and human resource professionals are receiving more attention. What used to be a slow-moving corporate technology space is now a booming market of HR cloud solutions to address the needs for the future of work. Most importantly, AI is helping companies find the best fit for skills within a chosen career path.
Knowledge workers may not be aware of the impact AI is quickly making in the way large enterprises manage their workforces. For too long, talent has been managed poorly, often relying on inaccurate job descriptions, uninformed interview processes, and leaning too heavily on writing the best CV. AI holds the promise that people can reach their potential, which benefits both employees and employers. In fact, this could fundamentally change the way we think about hiring. Connections and networks have ruled the employment world for decades. AI has the power to change that and hone in on true capabilities as the basis of hiring and promotion decisions. AI will also allow people to apply their capabilities to new industries. For so long, people have been laid off through no fault of their own. They worked in declining industries, and have struggled to translate their capabilities to new roles in new industries. However, AI is now able to match these people to a new job based on capabilities and potential.
Top 5 Tech Skills To Master in 2021
Tech Republic, December 21
If you are looking for a new IT job in 2021, there are five tech skills to master in the coming year. As a result, you will need to know which skills will give you the best chance at landing or keeping that position you want. Based on a survey of online course providers, tech experts, and C-level executives, the skills that will be most in demand in 2021 include cybersecurity, natural language processing, operational machine learning, and cloud-native architecture.
Cybersecurity is one key skill to master in 2021, as there is no shortage of cyber threats out there. Companies need to build in security at the start of cloud projects. If you can do DevOps and security, you will likely be more valuable. Automation is just one of the many AI-related skills that will be in demand this year. According to one survey, 70 percent of C-level executives now require employees to have automation skills. Natural language processing is yet another area with high demand. Voice is moving into more and more projects so speech recognition skills will be more and more valuable. Tools that can create to-dos from a meeting or make voice conversations searchable are just some examples.
The Top 6 In-Demand Cybersecurity Skills For 2021
CSO Online, December 15
Security leaders say there is not only a shortage in the number of qualified people working in the field, but also a real challenge in finding the needed skills among the existing pool of security professionals. That is perhaps not surprising, considering the lengthy list of desired skills needed today. In fact, security professionals need more than a single certification or even experience with a few key tools. Increasingly, they need the right combination of multiple security skills alongside technology, business, and interpersonal skills, as security jobs morph into a hybrid of roles that span different disciplines. The most in-demand security skills for 2021 reflect this trend, with security chiefs saying they need people who can pull together expertise in various sphere to meet the emerging security and threat environments as well as overall business requirements.
Risk identification and management is one cybersecurity area that will be very much in demand in 2021. Organizations want security workers who understand both the company and its industry. For that reason, veteran staffers can bring the business insights they need. And that insight, when combined with technical acumen and cybersecurity experience, helps them identify which threats pose the greatest risks to his company so they can effectively allocate limited resources to deliver the best protection. The best way to mitigate threats is to understand the risk, so organizations need people versed in governance and strategy who can then determine the best solutions, who can find the right technology or the right outside provider or build the right capacity in-house. Others also put risk management high on their list of desired skills for 2021, with Burning Glass listing it as one of the security skills seeing the fastest growth in demand over the upcoming five years and one that could earn professionals more than $10,000 a year in premium pay.
7 Things to Know Before Becoming a Developer Manager
InfoWorld, December 21
Heading into 2021, many developers will be thinking about the next step in their career, whether that involves mastering a new language or finally taking that move into management. Unlike many professions, software engineers do not have to move into management to progress in their career. There are principal and distinguished engineers as well as architecture and CTO career paths to pursue for developers who want to stay hands-on with the technology. But if you are interested in management, your key responsibilities become more focused on the team than your personal expertise or output.
First of all, know what you are getting into. In software engineering specifically, most managers do not see the move into management as a direct upward step on the career ladder but rather as a parallel track that requires a very different set of skills and priorities. From that perspective, engineering management is an alternate career track to software engineering. Somehow, a popular consensus has emerged that that once you have mastered the technical skills required for your roles and you have been senior engineers for a few years, the next step for you is to become an engineering manager. In such a way, becoming a developer manager or higher means learning an entirely new job. Your knowledge of programming and the culture of programmers are valuable tools but that is not what your job will be any more.
IT Careers: 8 Hot Jobs in 2021
The Enterprisers Project, December 21
The COVID-19 pandemic has forced many companies to reevaluate everything from their current tech stack to how and where their employees work. Many IT leaders will focus their resources on two critical areas: cloud and cybersecurity. Beyond cybersecurity and cloud, some more specialized roles are becoming increasingly valuable. Data scientists and Python developers saw an increase in demand in later 2020, suggesting that companies may be angling toward resuming business as usual, with a renewed focus on the data analytics and software building so crucial to overall business strategy. AI and machine learning experts, data experts, and process experts will also be indispensable over the next 12 months.
Topping the LinkedIn list of Top 15 Emerging Jobs in the U.S., with an annual hiring growth rate of 74 percent, is the AI specialist. A few different titles in this space, each with a very specific set of skills, will be in demand across industries, according to LinkedIn. Given the role that AI will play in driving data-driven decision making, resiliency, and risk mitigation, roles pertaining to AI will gain increased traction. Enterprises need an efficient way to scale their practices for AI implementation to accelerate their returns on investment. As a result, business intelligence-focused AI specialists will become important as organizations face increased pressure to optimize their workflows, and more and more businesses will begin asking BI teams to develop and manage AI models. Machine learning developers, responsible for building and scripting both supervised and unsupervised machine learning models and respective workflows, will also be key.
A Career Fueled by HPC
Communications of the ACM, January 2021
The path to a successful career in high-performance computing (HPC) starts by understanding the types of organizations in both the private and public sectors that are best able to leverage your unique skills and experiences to achieve their business goals. To put that into perspective, a long-time practitioner in the HPC field looks back at how she started in the field, which types of academic disciplines are best suited to a career in HPC, and the types of employers who showed the most interest in hiring, training and advancing the careers of HPC professionals. Since its early emergence in the 1970s, HPC has become indispensable to scientific research and discovery.
HPC is different from what is done at Silicon Valley companies such as Apple, Facebook or Google. HPC is all about using applied math to do science through the use of very large-scale computers. In such a way, organizations can essentially do expensive, centuries-long experiments via simulation on the computer. As a result, national laboratories that pioneered supercomputing fundamentally changed the scientific method from theory and experiment to theory, experiment and simulation. Large-scale computing has had a big impact. For example, among other things, knowledge of how parachutes work contributed to the development of air bags in cars. As HPC became more widely accepted, more data was collected and computers grew even larger, it led naturally to utilizing supercomputing for machine learning and what people think of as artificial intelligence.
Time to Exhume PSP?
Blog@CACM, December 14
Software quality matters, and that means industry practitioners should be focused on repeatable processes and approaches that they can use to produce high-quality software. For example, the Personal Software Process (PSP), developed by Watts Humphrey in the 1990s, prescribes a discipline that software developers should apply to produce good software and improve their professional ability over their careers. It has enjoyed moderate success but was never a mass movement and rarely gets mentioned today. However, it is still relevant for the current generation of software developers. With a few updates and revisions, PSP deserves to be known and applied. The most visible part of PSP is a six-step sequential process that builds on recommended practices and assessment criteria for software processes.
The core message of PSP is as relevant today as it ever was. That message is: we should learn from the practices of traditional engineers and apply a strict professional discipline. This includes keeping a log of all activities, keeping measurements of everything you do, estimating and planning your work, and understanding your current performance. Understand your programming style and how it affects various measures. As an example, code size, as a function of the number of routines, depends on whether you are more concise or more verbose in style. Continually improve your expertise as a professional. PSP gives concrete tools to apply the principles, with a view to measuring, tracking and analyzing your work; learning from your performance variations; and incorporating the lessons learned into your professional practices. PSP is a discipline of personal productivity and growth, emphasizing personal discipline, tracking and constant improvement.
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