Data science is the field that integrates domain prowess, programming expertise, and insights of maths & statistics to derive relevant information from data. Today, every organization necessitates a Data Scientist for appropriate use of the vast amount of data it produces and stores.

Data has become the most treasured resource on the planet, and it plays a critical role across all spheres, from pharma and marketing to consumer goods and even transport. Accordingly, companies are attempting to develop and elevate their data science teams as demand for data science talent is on the rise.

IT firms, whether established or a start-up, look at hiring a workforce that is future-oriented. Engineering graduates passing out are now expected to be skilled and adept in technologies like artificial intelligence, machine learning and data science. According to a recent report by NASSCOM, the demand for Data Engineering jobs are nearly 800K and is predicted to rise to 2.2 to 2.4 million jobs in 2024.

The pandemic has accelerated the digitisation beyond organisations, changed the aspects of the manforce and devised space for remote working which is the new normal across organisations.

Today's most jobs are focused on data, right from social media to apps that we use on a daily basis. All over the world, organizations are zeroing on methods to structure and harness the data for their decisive goals. Advertising, product designing, and even implementing strategy or campaign planning are fuelled by data. The jobs related to data are thriving across the globe.

Career Scope

A career in Data Science is up-and-coming. Increasing demands of data scientists in the current scenario, is being considered as the red-hot job for the decades to come. Scope of Data science is far-reaching and enticing. Being a data scientist encompasses a range of professions viz. engineers, computer scientists, statisticians, physicists, operations researchers, and machine learners.

If you are looking for a career in the realm of data science, the elemental skills required are ? critical thinking, organised approach, originality, intuition.

In addition:

• Knowledge of statistical and data mining techniques
• Command over programming languages, and satisfactory knowledge in machine learning and advanced analytics
• Ability to evaluate issues, pinpoint causes, and suggest solutions promptly
• Creativity to initiate new techniques

Another imperative factor of upskilling, students must be prepared to cope up with the basics of the technology and should be complacent dealing with digital technology which not only involves AI and ML but other modern technologies like Block-Chain, IoT, Robotics, etc.

Written By:

Punit Lalwani