“Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so data must be broken down and analyzed for it to have value.”
– Clive Humby, UK Mathematician, and architect of Tesco’s Clubcard, 2006
For the past few years, the entire world has been witnessing a steep and continuing upsurge in the amount of data. What’s even more interesting is that the rate at which the data is being produced is increasing exponentially as well. As Alphabet’s Eric Schmidt claims, every 48 hours, we generate the amount of data humanity has produced since the dawn of civilization until 15 years ago.
Data Science, therefore, has emerged as a discipline to manage, organize, and analyze this massive amount of data for profitable activities. Organizations from different industries are looking to hire data scientists and the market has become rife with opportunities for candidates interested in this field.
The U.S. Bureau of Labor Statistics sees strong growth for data science jobs skills in its prediction that the data science field will grow about 48% through 2026.
Since it is a relatively new career option, many people are confused as to what it truly entails. Let us put those queries to rest and take a look at what the future looks like for candidates looking to pursue a career in Data Science.
Career scope in data science: All you need to know
Who can be a data scientist?
While there is no specific degree that you need to become a Data Scientist, there are several certifications that you can pursue to tilt the odds in your favor. Many reputable organizations are offering extensive Data Science courses that help individuals acquire the skill set they’ll need to work in the industry as a Data Scientist. The more you work in the field, the higher you’ll get placed on the ladder of success. It is one of those fields where experience matters more than a degree.
As we discussed, there is no specific degree that you need to become a Data Scientist. However, the following qualifications can certainly give you an edge in the job market:
An undergraduate degree in computer science, statistics, economics and mathematics or a related stream
Working knowledge of Python, Tableau, R ,Advanced Excel, SQL, Machine Learning and Deep Learning
Having strong analytical skills is a bonus
A willingness to understand algorithms and a solid foundation in mathematics
Leadership qualities and a go-getter attitude
Challenges and solutions
Although data science has become a popular career choice, our country still lacks the infrastructure that is needed to produce market-ready Data Scientists. Following are the challenges and probable solutions that may help candidates looking to pursue a career in data science:
Lack of information
Many Data Science aspirants don’t know which course or certification to pursue to make themselves more employable. They can often be misled by brokers/counselors.
There is a need to spread awareness regarding the different options, and it can be done by leveraging different media channels and direct outreach programmes in schools and colleges.
The quality of education
Unfortunately, many institutions that offer courses on data science lack resources and skilled teachers, which is why they’re unable to deliver quality education.
In today’s fast-paced and dynamic world, syllabus and teaching methods have to be consta.,ntly updated to meet industry needs.
Lack of financing options
There is a severe lack of formal financing options in India which puts students under a lot of stress. If they want to pursue the course, they usually have to go for informal financing options, which can turn out to be very expensive.
Even if the financing options are available, the fees are so high that the candidates cannot pay the EMIs sustainably post-placement. For instance, several aviation institutes charge around Rs 3 to 4 lakhs as fees and manage to place the candidates at just Rs 10,000 to 15,000 a month. It, therefore, becomes extremely difficult for such candidates to pay the EMIs.
It is where novel fee payment structures like ISA (Income Sharing Agreement) can play a huge role. Under ISA, the candidates pursuing the course can pay the fees in installments once they start earning a sustainable amount of income. It could be a relief for several candidates who face financial constraints at the time of pursuing the course.
Not prioritizing placement
Numerous institutes in the country focus mainly on awarding degrees, but they lack the drive and resources to ensure placement which should be the end goal.
As is obvious, the institutes need to focus their energies on generating employment opportunities for their students. Raising the level of education and equipping the students with industry-relevant skills can help attract recruiters.
Authored by Nirpeksh Kumbhat, Founder and CEO, SkillEnable
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