ACM CareerNews for Tuesday, February 07, 2017
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 13, Issue 3, February 7, 2017
- 5 Tech Jobs That Will Boom in 2017
- Data Scientist, DevOps Engineer and DBA Among Top IT Jobs for 2017
- Want to Be a Software Developer? Time To Learn AI and Data Science
- The Rise of the Accidental Cybersecurity Professional
- 5 Steps to Finding Your Next Job
- What to Consider When Hiring Data Science Talent
- 7 Simple Tips for Beating Job Search Burnout
- 5 Common Tech Hiring Mistakes to Avoid
- Celebrating 50 Years of the Turing Award
- ACM's Open-Conference Principle and Political Reality
Looking ahead to 2017, there are several different tech jobs that are likely to grow in popularity, including jobs in areas such as machine learning and AI, big data, and cybersecurity. The important thing to keep in mind is that technology is constantly evolving, and so are the skills and the roles that are in demand by companies. At the same time that some tech jobs will boom in the year ahead, there are some that are likely to become obsolete.
Technologists specializing in building AI and machine learning products as well as algorithm creation will do well in the years to come. Instead of a programmer writing if-then-else scenarios, decision systems and algorithms are used now to make deterministic decisions based on real-time data. Big data is another expanding field. Companies have an embarrassment of riches when it comes to data, but making sense of it all and using it to driver greater innovation and market competitiveness is still a challenge. Every industry, from IT to marketing to finance, are hiring for data analysts that can help them make informed, quantitative decisions.
Career site Glassdoor has compiled a list of the 50 best jobs in the U.S. for 2017, and the three top jobs are all from the tech sector: Data Scientist, DevOps Engineer and Data Engineer. In addition, other top jobs included Database Administrator, UX Designer, and Mobile Developer. Jobs are ranked according to their overall score, which is determined using three key factors: earning potential based on median annual base salary, job satisfaction rating and number of job openings. The jobs that made this list performed highly across all three categories.
The position of data scientist leads with an overall score of 4.8 (out of 5.0), a healthy job satisfaction rating is a healthy 4.4 and a median base salary of $110,000. Currently, there are over 4,000 job openings for data scientists in the U.S. Also with a starting salary of $110,000 but with far fewer openings (2,725), is the title of DevOps engineer. With a job score of 4.7 and a job satisfaction rating of 4.2, DevOps engineers help organizations keep their application development and deployment effort on track. Data engineers (in third place) skilled in preparing data for analytics applications can expect to pull in $106,000 to start. Nearly 2,600 such positions remain unfilled in the U.S.
Artificial intelligence is almost certainly going to have a measurable impact on software development, with developers becoming more like data scientists. That means that companies could change the way they think about recruiting and retaining software developers. For example, AI and deep learning will change how software is written. The long-standing paradigm of developers spending months at a time simply writing features will change. The lesson is clear: for anyone planning to become a software developer, knowledge of AI and data science could be key.
With the continued growth of AI platforms, data will be increasingly incorporated to create the insights for software. Data will train the software to make it more intelligent. Data will drive the software release because the data is going to give the software the ability to interact. While parameters like interface and application flow will still be needed, data will drive the feature set in decisions on how the software evolves. Releases will be based on the software being trained to another level; updates will be based on new data sets and experiences.
The Rise of the Accidental Cybersecurity Professional
Tech Republic, February 1
With an extreme shortage of trained cybersecurity professionals, it's becoming increasingly common for people (and especially women) to enter the field from other careers, including IT, law, compliance, and government. These employees form a group of "accidental" cyber professionals who are filling the need for cyber professionals and offering a different view on security threats. At a time when the job prospects are excellent, though, women still make up only 11% of the world's information security workforce, and just 1% of its leadership. Part of the reason for this is that many women perceive that the only way of entering cybersecurity is through the technical door, but that's not the case: cybersecurity involves knowledge in tech, human behavior, finance, risk, law, and regulation.
Cybersecurity is inherently interdisciplinary. Depending on your background, you may be able to make the leap to security within your own company. There are many opportunities in cyber and many doors of entry. Whatever doorway you come through, you will be working with colleagues from many disciplines, and becoming more of an expert. It's a myth in the industry that you have to be technical to be in the field of cyber. Companies need people who have deep analytical skills, who can talk to clients, and translate technical speak to business value. That includes marketing and finance pros as well.
5 Steps to Finding Your Next Job
Entrepreneur, February 4
To make finding your new job as easy as possible, it helps to focus on a small set of no more than 10 target companies where you can make the biggest difference. From there, it’s time to start researching the specific opportunities that would provide the best fit for your own skills and experiences. One way to do this is via LinkedIn, which can provide insights into the types of people who get similar types of roles within your chosen industry. Also, use your LinkedIn connections that are employed at your target companies. What positions do they hold, and how are you connected to them? Explore the ones among those connections who are in a position to provide you with advice and information about the company.
Candidates need to use different avenues to do in-depth company research. To attract others to talk with you, you need to appear very knowledgeable and, hopefully, interesting to talk with. Find detailed information at your local library, by doing Google searches and by looking at Google Finance and Google News. Thoroughly study the company website, and look for your fit into the company culture. While there, check out the types of positions the company has posted, but at this time, do not rush to apply. First, you need to find an internal referral. This is a delicate phase, because if you have not done your work thoroughly and you pull the trigger too quickly, you might turn off the employee and miss your target. Excellent written and verbal communication at this stage is essential. Spend time developing your arsenal. Test it several times to see how effective it is. Before asking for referrals, make sure you’ve established a relationship first. Is there a way you yourself can help the employee you’ve connected with? Attempt to convince the employee to be willing to meet with you in person. That’s a success by itself. Ask about company culture, employment practices, whether it’s a fast-paced company and how employees are treated.
What to Consider When Hiring Data Science Talent
Information Week, February 1
When a company seeks to hire a data scientist, it's typically seeking someone with skills in advanced programming and statistical analysis, along with expertise in a particular industry segment. The need is great, and the skills gap is widening. However, dealing with the data science talent crunch isn't just about competing for talent: it also requires the right data science strategy to enable the analytics team to be successful. Most importantly, it requires the recognition that data science is a team effort. There are many facets to creating an effective data science team, including the proper balancing of functional and strategic tasks.
Part of the reason data scientists are so much in demand is because they have concrete skills in predictive analytics that others in IT and business roles lack. That being said, you’ll need sufficient talent and resources to both write and maintain software and algorithms while also gathering insights from internal teams and customers to customize and optimize the logic behind them. Companies need to set data scientists up for success with the right data management systems. High volume, multi-channel systems are very complex – and time consuming – to manage. Having a hub where data at the individual customer level is aggregated helps set the foundation for data scientists to really shine. Finding ways to automate processes so that the right data is available on demand will make any data scientist’s life easier and will make more possible under their strategic guidance.
7 Simple Tips for Beating Job Search Burnout
Fast Company, January 31
Looking for a job is a universal source of anxiety, and it can also be intimidating due to the seeming endless number of job postings that are available. The combination of both can lead many candidates to hit a job search wall, where feelings of excitement and optimism are replaced by feelings of fatigue and dread. Perhaps the most important thing you can do is to adjust your mindset. Instead of thinking of applications as a total time-waster, consider them the next (and necessary) step to scoring a job at one of your dream companies. With every application you submit, you’re that much closer to landing the right job.
When you’re job searching, you spend a lot of time at the computer. While looking for and applying to jobs online is important, too much of it could drive anyone crazy. Drag yourself away from your laptop to meet people who work in the field face-to-face. That way, you'll start meeting people who work in your industry, and you can start doing your homework to find the right fit for you. When you get home, research the companies where your new connections work to read employee reviews and get a deeper sense of what the company is about. Start with alumni networking events, which can be a fun way to reconnect with people you went to school with while talking about your job search—like mixing business with pleasure. A well-honed elevator pitch can be a great way to explain who you are and what you do, but sometimes you’ve got to go off-script to shake things up. The key to building relationships is establishing trust and likeability; so don’t always feel pressured to sell yourself when you meet new people.
5 Common Tech Hiring Mistakes to Avoid
Network World, January 31
Making the right hiring choice for your tech team is crucial, so you need to avoid the most common hiring mistakes to hire the best talent available and dodge the expensive and time-consuming pitfalls of getting it wrong. According to the U.S. Department of Labor, a bad hire costs at least 30% of the initial annual salary, but that number is believed to be much higher. It’s a mistake that companies simply can’t afford to make in today’s increasingly competitive marketplace. To help avoid the pitfalls of a bad hire and net the tech talent you require, the article provides five common hiring mistakes to keep in mind.
Companies looking for tech talent often operate under the misguided belief that they have the power since they are doing the hiring. However, when it comes to highly qualified, niche IT tech talent, that is no longer the case. Because specialized talent with technical expertise is so difficult to find and hire, qualified candidates are the ones dictating what job offers they respond to, which companies they want to work for, and how much they’ll be paid. To net top talent, companies must accept they are searching for talent in a candidate-driven market and act accordingly. Or, risk losing out on the talent they want to competitors that already understand this. Thus, if you want top tech talent, you’ll need to pay up. Since qualified candidates are dictating the market, they are demanding higher salaries. Current employee salaries are often one of the main stats candidates research to see if companies can match the rates highly qualified tech talent demands.
Celebrating 50 Years of the Turing Award
Communications of the ACM, February 2017
ACM President Vicki Hanson comments on the 50th anniversary celebrations of the Turing Award. Since it was first awarded fifty years ago to Alan Perlis for his work on advanced programming techniques and compiler construction, the award has been given annually, with the 50th Turing Award presented in June 2016 to Whitfield Diffie and Martin Hellman for their work on public key encryption. In total, 64 men and women from around the world have received the Turing Award, recognizing work laying down the foundations of modern computing. The prominence of the ACM Turing Award matches the impact of the contributions it honors. In the 50 years since its inception, the Award has become known as the "Nobel Prize of Computing."
To celebrate the first 50 years of the Turing Award, ACM is sponsoring a year-long series of programs, as highlighted on the Turing 50th website. This site consolidates information about the Turing Laureates and Alan Turing himself. It also presents the Panels in Print and provides information about the upcoming Turing 50th conference. “Panels in Print” is a series of writings on key computing topics of the day. The culminating event of this anniversary year will be ACM's Celebration of 50 Years of the Turing Award conference that will take place in June in San Francisco.
ACM's Open-Conference Principle and Political Reality
Blog @ CACM, January 31
ACM’s mission to advance computing as a science and a profession, enable professional development and promote policies and research that benefit society is based on freedom of thought and expression. That extends to the organization’s Open-Conference principle, which specifically notes that the open exchange of ideas and the freedom of thought and expression are central to the aims and goals of ACM and its conferences. Ultimately, this is a principle that embraces diversity and the freedom for people to come together to discuss ideas. The key question going forward is how ACM can remain true to this principle, despite the current political reality, in which diversity is now at risk.
In response to the Trump administration’s recent executive order on immigration, ACM expressed grave concerns and urged the lifting of the visa suspension so as not to curtail the studies or contributions of scientists and researchers. There are strong arguments against the constitutionality of the order, and lawsuits against the U.S. government have already been filed. But it may take months, if not years, for the legal process to conclude, and the outcome is far from certain. In the meantime, there will be continued debate about where to hold certain conferences. Some have even suggested that people boycott conferences taking place in locations that do not fully respect the Open-Conference principle.
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