3 Hottest Tech Jobs of 2018

3 Hottest Tech Jobs of 2018

A career in tech is one of the most in-demand jobs right now. That said, more and more companies are willing to invest in these talents. From data scientists to product managers, the competition between companies is expected to be tighter in the next couple of years. Businesses foresee the potential in tech. Even if they are not literally a tech company, they try to be one in order to keep up with the corporate competition.


Whether you are a fresh graduate or someone who wishes to change a career path, a career in tech is one of the best choices you can make. If you have been stagnant in your career for quite some time now, it’s time to re-evaluate your options. Of course, technology is not the only great job in the planet, but it is one of the most stable job there is.


Here are the hottest tech jobs of 2018:


  1. Data Scientist
    Data Science has been labeled as the best job in America for three consecutive years and is still the most in-demand tech job right now. A data scientist is responsible for extracting, gathering, analyzing, and interpreting data in order to create real-world solutions. Big industries such as the health industry and the finance industry are in demand of more data scientists to help them better operate.

  2. DevOps Engineer
    The growth of demand for DevOps Engineers are exponentially increasing. Next to data science, DevOps is second in having the highest job openings out there. More companies are expanding their operations thus requiring the talents of DevOps. These companies are also careful in choosing the right candidate for the job. That said, if you are looking forward to have a career as a DevOps Engineer, you need careful research and preparation to increase your chances of getting hired.

  3. Mobile App Developer
    Because of the success of numerous mobile apps, more companies also want to keep up in order to succeed in their line of business. The lack of training in mobile app development in universities today has caused the hiring process to become tough for employers. Right now, it seems as though everything can be done through mobile phones. From buying groceries to banking, it seems like everything is just at the tip of our fingers. Companies who don’t utilize this trend seem to lose to those who keep up with technology.


A piece of advice – just because tech jobs are increasing doesn’t mean that anyone can just easily take it. It is still important to hone both your hard skills and soft skills in order to succeed. Also, one’s attitude and character will greatly affect one’s chances in landing a job.

How to be a Successful Data Scientist

How to be a Successful Data Scientist

If you wish to become successful in data science, you are in for a lot of surprises. This field is neither quick nor easy but if you are persistent in becoming one, you can be successful like the others who worked hard and persevere. But before you join the game, you have to consider some dark areas like, the expanse of your knowledge on data science, your computer skills, and which resources to use.

Data scientists are said to be open for experimentation and committed, but most of all, willing to invest effort and money.

Data mining and statistical analysis retained the number two job spot in recent years. Both skills are under the umbrella of data science. The word data science was coined by Professor William S. Cleveland of Purdue University’s Statistics department upon advocating the statistics and computer science merger.


Data Scientists in Brief

Data scientists use their knowledge of modeling and statistics in converting data into actionable ideas. Stating with product development, the wide scope goes through customer retention to new trade opportunities.

Due to the growing demand of data science, employers are eager to hire talents with years of experience. It also opens up opportunities for mid-career professionals as well as college students.


Skills Required

To be a data scientist, you need to have combined knowledge of analytical, presentation, and technical skills. These skills are hard to find altogether in a worker but with practice and motivation, nothing is impossible.

Other skills should be knowledge in applied mathematics and statistics. Ideal data scientists should know how to test hypothesis using their designed experiments, have ample programming skills good enough to construct methods of processing, storing, and sourcing data.

They should be fine with translating their findings by using storyboards or data visualizations, and most of all being knowledgeable with SQL, Python, Tableau, SPSS, adoop, and R.

Several schools are now offering specialized programs to fit data science. There is no need for a PhD for this particular field although some of the better data scientists have them already.


There are three usual avenues that lead to data science and these are the following:

  • Master’s Program
    Enrolling in a master’s program can be time-consuming but the structure it provides places the students directly near on-campus recruiters.

  • Massive Open Online Course
    Some online courses are incomplete and learning is done by the students themselves. Finding a job depends on the student and their expertise.

  • Bootcamp Learning
    The timeline for this type of learning is actual but accelerated and usually conducted by practitioners of the field. Approach is based on experience. Finding a job can be easy with the help of staffing managers who have direct contact with employers.


On top of these options, you can apply in a company that seeks for skills you already have so you can get experience and a chance to connect with prospective employers.