What to expect in the next 3 years as a Data Science Professional in the Big Data Industry
The data science industry did not exist 10 years ago. It manifested through the rise of big data and the new-found ability for businesses to understand and utilise the untapped insights with their abundance of digital data.
This has changed the way companies solve their business problems and new jobs are being created. Today, careers are being transformed quickly through the evolving nature of the data science industry, the global skills drought and demand from employers determined to hire for their data needs.
So, if you’re currently looking to progress your career within the big data industry – here’s what to expect in the next three years:
1. International Career Prospects
As businesses worldwide become more data oriented in their business practices, they need to hire specially trained data science professionals. As the industry is still new, there has been an influx of big data jobs but a growing global skills shortage.
Businesses from around the world are beginning to analyse, organise, extract insights and predict from their digital data. This leads to evidence-based business decisions, improved business processes and product offerings, increased customer satisfaction and revenue. Steering their businesses into the data driven age, they also create thousands of new jobs for tech savvy individuals with an aptitude for data handling.
In fact, according to a report by PwC, 2.7 million new data science and analytic jobs will be created by 2020. So, as a trained big data professional you will be equipped with the skills desired by employers internationally, resulting in your job prospects no longer limited by your location.
2. Evolving Jobs Market
When every business around the world is seeking professionals with data science, analytics and machine learning capabilities, the jobs market has not only increased by the number of jobs, but the job requirements and job descriptions have also evolved. This is to match and represent the growing needs of different industry sectors. This trend is expected to continue into the next decade as businesses are pursuing more specialised data solutions to their business problems.
For example, a marketing firm may prefer you to have knowledge in marketing, digital media, consumer research, and sales combined with qualifications in data science. The same way, a financial advisory firm would be more inclined to hire you with data science qualifications if you also have a background knowledge in accounting, finance, economics, or business analytics.
3. Exponential Earning Potential
Where there is a skills shortage, there are employers looking to pay more for a job well done.
One of the obvious benefits of becoming educated and trained in data science is the lucrative career opportunities and job prospects awaiting your application. As job requirements and data tools and technologies continue to advance, so will your earning potential as a big data employee. As you are required to do more in your day to day to keep up with employer and industry data demands, you will have the advantage of working in a growth industry – where the volume of data is growing and where salaries are big and the career prospects are even bigger.
In comparison, the average 2018 Data Scientist Salary in the US was USD$131K (averaging AUD$181k). Australia generally lags the US tech market by 3 years and due to our growing skills shortage and based on industry salary projections by the Asia Pacific Economic Cooperation, we expect data scientist salaries to rise to AUD$150k-180k by 2021.
4. Professional Skills Advantage
Individuals looking to upgrade their qualifications to data science, analytics and machine learning have the power to satiate the global skills drought and become equipped with an in-demand skill set that will make employers seek you out and put you at a professional skills advantage.
However, the other side to a professional skills advantage, is that you need to work hard to maintain that level of expertise to stay desirable to employers. As technologies develop and the job demands increase, so will the integration of automation technologies across industry sectors. As advised by APEC, to avoid becoming obsolete – it is the responsibility of the big data professional to adapt and keep up their skills based on business needs, because big data professionals with fresh skills that are taking the initiative to learn new technologies, will not be easily replaced by automation as they are willing to progress with the industry.
5. Forefront of Technology Innovations
One of the exciting aspects of a career in data science and analytics is that you will have the opportunity to experiment and work with new technologies as they develop. You will get to use them to solve complex data scenarios, improve business processes and formulate tech-savvy solutions.
For example, the biggest change in data science and analytics processes in recent years has been the introduction and rapid increase of cloud computing. Here are 3 ways cloud computing has impacted the big data industry:
By using a shared online network, cloud computing has essentially enabled anyone with data that needs to be handled and stored, to gain access to powerful computing services through the connectivity of the internet. This has allowed businesses to save time, money and physical resources and transformed their data management processes.
The integration of cloud computing in industry, is what made it possible to analyse copious amounts of data to reveal valuable, previously untapped insights about a business. This has given enterprises, SME’s and start-ups the ability to make smarter, time sensitive and data driven decisions – resulting in a better understanding of their customers and competitors.
The popularity and efficiency of cloud computing has also created space for new developments in the realm of open source data science tools and applications, as well as new and improved machine learning and automation technologies. This has increased the rate at which big data is processed and also created new opportunities for data collection.
If you’ve been thinking about making a career transition into the big data industry, the next 3 years are about to see the skills gap increase, a vast influx of data science jobs and the continued rise of the data economy – now would be a strategic time to upskill your qualifications to data science and become a part of a booming industry that hasn’t even reached its peak.