A Data Scientist is a problem solver who solve complicated problems from business users.
They want to forecast something; they want to understand how data can improve their business. They figure out – how can we utilise that data to actually provide value to the business. They use different tools for different visualizations and then make sense out of that data. Being a data scientist is the challenge. It’s almost like being an investigative journalist, investigating a story; you never know what are you going to find when get your hands on this new set of data.
According to Harvard Business Review, a Data Scientist “is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data”. With experts predicting that 40 zettabytes of data will be in existence by 2020 , Data Science career opportunities will only shoot through the roof!
Shortage of skilled professionals in a world which is increasingly turning to data for decision making has also led to the huge demand for Data Scientists in start-ups as well as well-established organizations. Presently, there are only 10,000 - 15,000 analytics and data experts in India and there will be a shortage of 2 lakh data scientists in India over the next few years
A Data Scientist dons many hats in his/her workplace. Not only are Data Scientists responsible for business analytics, they are also involved in building data products and software platforms, along with developing visualizations and machine learning algorithms.
The opportunities in Data Science are huge.
Job roles in Data Science :
· Data Scientist
· Data Architect
· Data Administrator
· Data Analyst
· Business Analyst
· Data/Analytics Manager
· Business Intelligence Manager
Salary of Data Science professional:
The median salary for a Data Scientist role is Rs. 1,213,413 according to a survey.
To remain ahead of the curve, technology professionals need to have the right combination of knowledge and skills.
Having a solid academic foundation in the core concepts of Data Science and ML, along with a deep understanding of their applications will enable professionals to stay relevant in the rapidly changing ecosystem of the technology industry.