ACM CareerNews for Tuesday, June 5, 2018
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Volume 14, Issue 11, June 5, 2018
With the potential of big data to change the way every company operates, data jobs within the tech industry are exploding in popularity. Currently, experts forecast annual growth rates of nearly 12% for data-related tech jobs over the period from 2018-2024. That type of long-term sustained growth is helping to shine a spotlight on some of the most in-demand tech and data jobs for 2018. One of the most popular data jobs is Data Scientist, which routinely is listed as one of the best jobs in America, thanks primarily to its six-figure median base salary and high job satisfaction rates.
In addition to Data Scientist, another popular data-related tech job is Business Intelligence Analyst (BIA). These professionals use data to inform their recommendations to companies and help guide decisions based on the market or trends. To leverage these trends, business intelligence analysts are always combing through data to identify new opportunities for companies and articulating the business meaning of the data results to stakeholders. Database Developers are also very much in demand. As the job title suggests, a Database Developer is focused on improving databases, creating new applications for databases or modifying legacy applications to work with a database setup. The average annual salary for a database developer is about $90,000.
Many of the most valuable venture-backed tech startup companies are venturing outside their high-cost headquarters and setting up secondary hubs in smaller cities. As a result, cities such as Nashville, Phoenix, Portland and Raleigh are seeing an influx of new startups. Since most of the biggest and most lavishly funded startup companies are based in high-cost locations, like the San Francisco Bay Area, Boston and New York, it makes business sense that they are now looking to set up offices in smaller cities with a lower cost of living.
Nashville and Phoenix are two of the primary hotspots for so-called unicorns (startup companies valued at $1 billion or more) setting up secondary offices. Many other cities are also seeing some scaling startup activity. For example, the Research Triangle region in North Carolina is known for having a lot of STEM grads, so it makes sense that tech companies headquartered elsewhere might still want a local base. Orlando and Portland also stood out as hub cities that are attractive to tech employers and hot new startup companies.
The list of top 10 U.S. cities for blockchain jobs right now includes San Francisco, New York, Chicago, Los Angeles, Boston and Seattle. To gain a comprehensive look at the blockchain job market, a recent survey examined more than 3 million job listings across four sites, as well as the number of blockchain startups, new companies, crypto funds, and overall employment market in U.S. cities. This results in a more thorough examination of the climate for blockchain jobs than simply viewing open jobs on websites, and also serves as an indicator for potential job market growth.
San Francisco only narrowly eclipsed New York for the No. 1 spot on the list. But while it has far fewer job postings than New York, this California city dominated nearly every other category, including top blockchain companies, blockchain startups, and blockchain investment funds. It also had a strong overall job market. San Francisco is home to leading crypto exchange Coinbase, cryptocurrency and payment solutions companies, and some very established crypto hedge funds and VC funds. New York has more than twice as many blockchain job postings as any other city, though comes in second to San Francisco in terms of blockchain companies and funds. New York is home to a large number of crypto hedge funds and venture capital firms, as well as Wall Street banks that are beginning to implement blockchain-based payment systems.
Everything You Need To Know About a Career in AI
Silicon Republic, May 17
Jobs in artificial intelligence already exist, with AI architect considered one of the hottest jobs of the future. But how do you actually switch into a career in AI and automation? The first thing you need is an understanding of the different levels of expertise within AI. Within the broad umbrella term of AI, there is a combination of roles at various levels of expertise. The most popular roles include data architects, software engineers and machine and deep learning engineers.
When it comes to AI, it is not just a matter of the technology advancing to a point where jobs leveraging automation and artificial intelligence can exist. Research from September 2017 published in MIT Sloan Management Review shows that almost 85% of business executives believe that AI will allow their companies to obtain or sustain a competitive advantage, but only about 20% have done something about it. Despite wanting and needing to develop alongside AI, businesses are reluctant to truly embrace the change, and this can have a knock-on effect when it comes to up-skilling and developing the talent. There are a huge number of jobs that will become available soon, and some promising ones already exist. These include automation specialists, customer success data scientists and process optimizers.
6 IoT Skills That Will Future-Proof Your Career
Network World, June 3
If you are thinking about developing your career for the next wave of technology innovations, the Internet of Things continues to be a hot area to pick up some in-demand skills. Earlier this year, Gartner predicted that 20.4 billion IoT devices will be connected in 2020. This influx of new IoT devices will lead to tens of thousands of new jobs in the IoT economy. The 6 IoT skills you will need in the future include those related to sensors, communicative chips, communication gateways, cloud management, security solutions, and domain knowledge that identifies and addresses problems with IoT.
Building useful devices that are able to sense, act, compute and communicate with the IoT network is a critical part of the IoT infrastructure that companies need to move forward. This includes sensors that can detect position, pressure, flow, acoustics, humidity, light and temperature. The most functional and accurate sensors will be invaluable contributors to the future of IoT. Analyzing data in the cloud and providing feedback to the IoT device is critical. Experts emphasize the importance of such skills as being able to work with unstructured data, complex event-processing using tools such as Apache Spark, machine learning for cognitive computing, and data visualization that can identify data patterns and structure. In addition, engineers who are able to apply strong security measures and controls both to IoT devices and to the data they process will be increasingly in demand.
Does That Smart New Software Developer of Yours Also Have Soft Skills?
Entrepreneur.com, May 23
Current trends in software development suggest that companies need to hire programmers who have developed not just software skills, but soft skills as well. In fact, some recruiters point out that STEM expertise is no longer the most important indicator of employee success. Unfortunately, many smart new developers have either neglected or missed the opportunity to build communication skills and other soft skills. Contributing to this problem has been the fact that educational institutions and companies have not provided the necessary training or support to build these soft skills, either.
The current business models used by tech companies require more communication than ever before. Companies have long outsourced certain business processes as an effective cost-saving strategy, particularly for technical or resource-intensive jobs like software development. Whether outsourcing to distant overseas locations or to a nearby country, developers need to work together across different languages and cultures, and that means developers more and more need to be able to communicate effectively. Developers who excel in empathy, listening and the ability to receive feedback will be good at communicating with both one other and their clients to meet client needs. The best developers are those who ask a lot of questions and never make assumptions about a project. These individuals not only have a clearer understanding of what needs to be done, but stay motivated to achieve it.
Data Scientist Is Still the Hottest Job in America
Bloomberg, May 18
Companies and recruiters are actively seeking to hire data scientists, and that is leading to a shortage of people with the requisite skills for data science. A lot of people are transitioning from other fields like economics, psychology and mathematics, because they see the field is exploding and salaries are inflating. People with data science backgrounds are among the most sought-after professionals in business, with some data science candidates commanding as much as $300,000 or more from consulting firms.
Job postings for data scientists rose 75% from January 2015 to January 2018 at Indeed.com, while job searches for data scientist rose 65%. A growing specialty within the data science field is sentiment analysis, or finding a way to quantify factors that had until now been considered very subjective and qualitative. A typical data scientist job pays about $119,000 at the midpoint of salaries and rises to $168,000 at the 95th percentile, according to staffing agency Robert Half Technology. In many cases, candidates with the right skills are receiving at least one serious inquiry a week from recruiters trying to hire them away for other opportunities. In other cases, companies are offering more perks, including the ability to telecommute.
How We Can Better Prepare Graduates For a Job in the Cybersecurity Workforce
Infosecurity Magazine, May 2018
There are many steps that universities can take to better prepare recent college graduates for future careers in the cybersecurity area. For example, the curriculum that is taught at universities needs to be more aimed at preparing graduates for jobs. Students are promised, and shown by colleges, the statistics of job employment after graduating from their program, but the skills they walk away with are often lacking. A recent survey states that almost 74% of recent graduates reported feeling as though their colleges and universities had failed to fully prepare them for their post-grad careers.
Rather than preparing college graduates to play an important defensive role against cyber attacks, many colleges require graduates to take classes that are not necessary for their chosen profession and may not have any practical application. Because of this, when graduates are applying for jobs, they are often passed over for lacking the skills necessary to match their employers needs. According to a recent survey, 84% of employers believe half or fewer cybersecurity applicants are qualified for the position. It is clear that there is a need for curriculum modification to help improve the skills of students. There are currently over 200,000 cybersecurity jobs in the U.S. that are unfilled, and this skill shortage is a key reason why. The only way to address the demand of suitable candidates is to modify current curriculum for current technology needs.
Teaching Two Programming Languages In the First CS Course
Blog @ CACM, May 22
One question that continues to intrigue computer science educators is whether teaching two or more programming languages in the first computer science course will help students to master key concepts faster. A related question is whether teaching a second language sooner can lead to better learning, transfer, or development of abstractions. To answer those questions, researchers have started to analyze the transfer process between programming languages such as Lisp, Prolog, and Pascal. What they found is that it is difficult to transfer coding skills among programming languages. However, students have an easier time understanding common functionalities, such as variables, list structures and iterative processes.
For now, it appears that it is difficult for a novice to move easily between one programming language and another. Student knowledge of programming tends to be tied to a specific programming language and the textual details of that language. While students can transfer knowledge of algorithms and how to plan programs, it is harder for them to represent that functionality with coding and syntax. It is now evident that student knowledge of programming is tightly tied to the syntax of their first language. You can teach concepts separate from the programming, but that does not necessarily help with transfer. Knowledge of concepts like variables and lists will transfer, but only once students have that knowledge. Students are going to successfully transfer from one programming language to another only once they have developed deep understanding of the first programming language. If you move between languages too soon, students just struggle with the different syntax elements, and the switch may actually delay their development of the deeper levels of understanding.
Communications of the ACM, June 2018
ACM recently celebrated the top innovators in the field of computer science. At a gala event, John Hennessy and David Patterson received the prestigious A.M. Turing Award for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry. Their primary insight was to find a method to systematically and quantitatively evaluate machine instructions for their utility and to eliminate the least used of them, replacing them with sequences of simpler instructions with faster execution times requiring lower power. In the end, their designs resulted in Reduced Instruction Set Complexity (RISC), which is used by most chips today.
The second most prestigious award from ACM is the ACM Prize in Computing and the 2017 award goes to Dina Katabi of the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (MIT CSAIL). Her contributions to wireless communication and applications are both deep and broad. Concerned about interference in wireless networks, Katabi developed the concept of network coding, in which messages are encoded and re-coded as they move through a network in such a way that increased resilience and capacity can be achieved. She also pioneered creative work on the use of Wi-Fi signals, such as the ability to perceive objects and life forms on the other side of walls opaque to visual frequencies.
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