Did you know that the best jobs right now include titles like Data Scientist, Data Engineer and Business Analyst?
In 2015, there were around 2.3 million open jobs asking for analytical skills and by 2018 the forecast of population with analytical skills is going to be around 2.9 million.
Therefore the landscape of jobs requiring data science and analytics competencies and skills really needs to be looked upon, which means this problem is insurmountable.
Which also means that the scope of data scientist is going to expand in the coming years giving better opportunities to candidates aspiring to be a data scientist.
According to IBM, by 2020 the number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings to approximately 2,720,000.
The democratization of data is tremendously transforming our world, sensors are everywhere. Cities and everything depend upon a wide variety of data sources now. The governments at all levels are opening their data to the citizens. Old businesses are being transformed by data.
That means, workforce needs have shifted rapidly and there is a huge demand for new breed of professionals skilled in data, analytics, machine learning and artificial intelligence requires a requisite response from both higher education and workforce development.
Will there be enough data scientist by then? And how will this lacunae be filled?
- To close this gap, workforce development and education sectors must look beyond the data scientist and develop more roles such as data engineers, data governance, data privacy, data security specialist and data product developer etc.
- Data democratization impacts every career path, hence academia must strive to to make data literacy an option for every student in any field of study.
- To meet this demand, businesses need to rethink hiring and training.
- Higher education need to be nimble and responsive.
What you don’t know: Data Science and Analytics are not just the buzzword now but are essential tools. Every single day, 2.5 quintillion bytes of data are created.
What are the findings so far?
The demand for Data Scientist jobs is projected to grow by 15% over the next five years, which translates to nearly 364,000 new job postings expected nationally by 2020. The fastest-growing roles are Data Scientists and Advanced Analysts, which are projected to see demand spike by 28% by 2020.
What you can do today?
Analyzing that these job roles are in demand today, you might want to consider choosing this as your next career role. These hybrid jobs require deep expertise in multiple functional roles , but why not take that chance and be the next data scientist. To be a one, you require skills such as SQL, Big Data, Predictive modeling, Statistics, Mathematics, Machine learning, R & Python programming along with expertise in marketing, product management and market strategy.
Why you should choose data science today?
Because it is the most demanded, fastest growing, highest paying and the hardest to fill analytical skills.
- Key skills and high paying skills by occupation
- Analytical Scores and Key Analytical Skills in non-Data scientist Occupation
- Demand of Data scientist by industries
How can I build my own career and narrow down data scientist as my next job profile?
Here are three strategies you can consider now:
- Start building and upgrading your skills by getting trained from the experts in the industry.
- Do live projects so that this will add a plus point to your resume while showing your skills over the domain.
- And voila get hired.
Where do I start from?
While skills in Python or R may be preferred now, for example, a competent coder can and should demonstrate the ability to learn analytical skills and programs. There is this online career path likethat can help you understand how to signal for the right skills, while getting to work with live projects is an added benefit. They not only offer you with hands-on training but also assure a job in a product based startup and companies etc.
P.S. Learn while you still can.
Hope this clears your doubts.