Career Option In DATA Science: Opportunities In India

Data Science, therefore, has emerged as a discipline to manage, organize, and analyze this massive amount of data for profitable activities.

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.”

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.

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.

Courses In Data Science:

• Machine Learning: Machine learning is a method of analysis of data that automates analytical model building. It is an integral part of data science courses based on the idea that models can learn the data, identify patterns and make future decisions and predictions with minimal human intervention. The average salary ranges from INR 3-8 LPA in India
• Bio Data: Big Data is the collection of huge volume data, growing exponentially with time, the data can be structured, semi-structured, or unstructured. Several training institutions and websites provide Big Data Courses starting from short-term certificates or diploma/ PG diploma courses to long-term degree courses. The average salary offered to big data professionals ranges from INR 2-9 LPA in India.

• Artificial Intelligence: Artificial Intelligence is related to building smart machines capable of performing tasks and mimicking humans. It is the simulation of human intelligence in machines. The candidates can become AI Specialists, AI engineers, AI developers, Robotics Engineers, Robotics Automation Engineer, Data Mining Analyst, Machine Learning Engineer, etc. after artificial intelligence courses. The average salary ranges from INR 7-15 lakh per annum.
• Predictive Causal Analytics- Through data science courses, you can make a model that can predict the possibilities of a particular event in the future. For example, data science models can perform predictive analytics on the payment history of the customer to predict if the future payments will be on time or not if you want to see the probability of customers making future credit payments on time.

• Prescriptive Analytics- Data science courses enable users to make a model that has the intelligence of taking its own decisions and the ability to modify decisions with dynamic parameters.
• Machine Learning for Making Predictions- Data science courses can make a model which is a fraud detection model that can be designed based on the historical records of fraudulent purchases in a major finance company.
• Machine Learning for Pattern Discovery- Data science courses also enable models that can predict future events without any inputs of past trends and data, which is commonly known as pattern discovery. The most common algorithm used for pattern discovery is Clustering.
• Data Science Specialization:

• Cloud Computing: Cloud computing is the delivery of computer-related services, including servers, storage, database, software, analytics, over the Internet to offer rapid innovation and flexible resources. You are free to pay only for the cloud services you use, helping lower your operating costs, and run your business more efficiently. Cloud computing offers many advantages such as efficient cost, speed, reliability, and security.
• Cyber Security: Data is being created at exponential rates. It includes our social media photos, search history, and many other data sets. It is the responsibility of the companies that hold such data to make sure that they are secure. Cybersecurity deals with the techniques and software used to protect data and systems.

• Steganography: Steganography is the art of encrypting, embedding, and hiding confidential information in Pictures and Videos. Data is the foundation of any business. The interactions through data remain an integral part of a business. Thus, being able to utilize data efficiently, without the fear of being breached, is a major goal. Steganography is the major data encryption tool in the IT industry, especially when data is being transferred via Bluetooth.
• Ethical Hacking: Due to the increase in the number of cyber attacks, data science companies look for ethical hackers to secure their data from the black hat hackers who are involved with illegal activities. Ethical Hackers are professionals who are granted access to the network by the authorities and then report vulnerabilities in the data set and systems. 

Bachelor Courses Available On Data Science:

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 constantly 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.

Even West Bengal Government Student Credit Card scheme provide effective financial support to students in order they can avail the opportunities.

Pros of Becoming a Data Scientist

The major pros of becoming a data scientist are its excellent job prospects, number one career in demand, the versatility of work it has to offer, and the challenges it holds.

• Excellent job prospects: According to LinkedIn, a Data scientist is one of the most promising job prospects, with an average salary of $130,000 per year. The Bureau of Labor Statistics predicts a 16% job growth rate for data scientists; that’s nearly three times the growth rate of the overall job market. 
• Versatility: Data scientists can work in different sectors, such as healthcare, baking, e-commerce, marketing, and consulting. In addition, data scientists can work in government, academics, private, and NGOs.
• Challenging work: Data science combines mathematics, statistics, computer programming, and strategy, hence, a career in data science is beneficial for those who like solving puzzles and other brain-teasers.

Cons of Becoming a Data Scientist

Data science is one of the most promising careers, yet there are some challenges to being a data scientist. Issues of privacy, diversification, rapid changes, and a general approach are prevalent.

• Privacy Issues: Online privacy is one of the most challenging issues when it comes to being a data scientist. The ethical issues of gathering and use of these data are prevalent and unlikely to be resolved anytime soon.
• Rapidly Evolving Career: A data scientist has to stay up-to-date with advances and best practices in data science to remain relevant and in-demand. This holds for all professions, but especially in fields like data science, where changes can be rapid and dynamic.
• Male-Dominated Profession: With a 7:3 male to female ratio, data science concludes to be a male-dominated profession. Many data science companies are already looking to diversify, by recruiting more women and people of different cultural backgrounds. 
• Generalist Approach: There is no industry-standard definition of the work and tasks of a data scientist. A data scientist has to be an expert in machine learning, engineering, statistics, and analytics.

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.