Is it December already? Where did 2019 go?
The data science industry hasn’t gone down though. It is now that we’re experiencing the industry becoming normal and data scientists upskilling with the latest data science skills. Barely, we find a day that passes by without hearing a buzz from the tech industry.
2020 will be a year where data science professionals will still seek to fill in vacancies in companies thriving to look for data science solutions. Though the data industry a thing of the past, it is still not dead, there’s still a lot to be excited about. Especially for those looking to forge a career in data science, 2020 will be a fruitful year.
· IBM announces the rise of 364,000 to 2,720,000 job openings in 2020. Job growths will experience rapid growth of up to 700,000 openings.
· A data science career will remain to be the number one job listed in Glassdoor and will remain unchanged until the foreseeable future.
· Data scientists to grow by 28% in 2020, as predicted by IBM.
· 11.5 million jobs to be created by 2026 says the U.S. Bureau of Labor Statistics.
How data science is becoming a mainstream career?
Due to technological advancements, data science is now moving closer to becoming a crucial part of most organizations.
This will not only boost newer job opportunities but will also make this much more accessible for individuals with proper training.
For instance, a taxi driver used to be one of the most incredible knowledge-intensive jobs since they’re required to have extensive knowledge regarding the city’s layout. But thanks to GPS apps. Today, drivers only need to follow directions from the voiceover and take routes as instructed.
Data science will see a similar pattern with the rise of machine learning and AI. For an aspiring data science professional looking to become a machine learning engineer, you will need to have extensive knowledge of Python programming and a good amount of knowledge in constructing neural networks.
Despite having a certain amount of programming packages that make it easier to build machine learning models, it is still mandatory to have a solid understanding of the underline computer science. This ideally applies to individuals with no understanding of computational thinking.
And since data science and machine learning have become the mainstream for most companies today, it is now becoming user-friendly. No code tools will be allowed to those looking to perform statistical analysis even without prior knowledge of math or programming.
One of the biggest examples is AutoML. Even without prior knowledge in coding and neural networks, the user can easily upload a few data set, and within a few clicks prediction algorithms can be performed for text classification or sentiment analysis.
It is not an easy task for someone to build a machine learning model that could identify thousands of categories from scratch, that too for someone without coding knowledge. However, with AutoML, it barely took the person more than a few clicks to run their algorithm and predict data that wasn’t seen before.
For instance, if you type a phrase in the user interface that says, walking among trees. The AutoML will quickly predict the most likely category i.e. exercise rather than picking the categories such as bonding or achievement.
However, tools like AutoML are still not enough to become a great data science professional although it is a good illustration.
Not to forget the rise of demand for data scientists has prompted online education programs to include the latest data science skillset in their coursework. Besides coursework, online training programs and live industry projects are given to individuals aspiring to become tomorrow’s data scientist.
As a result, top employers and organizations will be keen on hiring a certified data scientist for their firm. This simply means competition will be fierce in the coming years.
A data scientist will not only hold responsible to predict the future of the organization but will help businesses excel. How ready are you today?
