Home > Blogs > How Data Science Will Evolve in an Increasingly AI-Driven World
How Data Science Will Evolve in an Increasingly AI-Driven World
By Arijit Banerjee
Rapid advances in digital technologies, data, and analytics are transforming the role of data science in the future of work. While the popularity and excitement around data science is at an all-time high, how organisations value the data science discipline depends on whether they are digital-natives or non-natives. Most organisations have a dedicated data science team but giants like Netflix, Airbnb, Amazon, and Google, who claim to be completely data science driven companies employ data scientists in every business function. Companies who report phenomenal success with data often go a step further and employ another ace up their sleeves – Artificial Intelligence (AI). Combined with data science, AI presents an incredible opportunity to handle humongous amounts of data, derive meaningful insights, and enable intelligent decision making. But while data science as a career is the hottest one right now across the world, with demand far exceeding supply, this doesn’t take away from worries regarding its obsolescence in future. Nowadays, forward-looking youngsters are afraid to take the plunge into data science, thinking Machine Learning (ML) and AI will eat away their jobs in 20 years.
Fortunately, most of those concerns are pointless. What data scientists need to realize, instead, is that only routine data science functions such as data aggregation, collation, cleaning, and reporting will be increasingly automated and handled by robots in the future workplace. To remain relevant, data scientists will need to evolve in their roles by acquiring AI handling training to be able to tackle higher projects and drive value.
The new skills that data scientists need in an AI-driven world
Though programming, statistics and quantitative analysis still remain as must-have skills if one aspires to become a data scientist, knowledge of machine learning has become the new imperative on job. This is because AI has penetrated every ounce of data science and even data scientists who don’t implement ML models themselves, can benefit from learning the fundamentals of ML in order to create prototypes to test assumptions, select and create features, and identify areas of strength and opportunity in existing ML systems. Data science knowledge coupled with ML training is particularly sought after in fields such as statisticians, physicists, operations researchers, and others who have to develop top-down or bottoms-up models to address business problems.
The real work of a modern data scientist is to analyze and model the data
While knowledge of technical programming languages such as R and Python are undoubtedly important, a modern data scientist must acquire and continuously brush up his/her AI and machine learning skills because working with ML libraries and data visualization libraries is a key aspect of the job. The real work begins after data cleansing and involves a fair degree of data modeling, making basic (for entry level jobs) and advanced (for mid-senior positions) AI skills a critical imperative. The bottom line: traditional approaches towards data science no longer suffice in the modern world as they are both resource and time exhaustive, while ‘real-time’ is the new imperative for success. AI with its capability to fast track data interpretation and generate actionable insights, will offer data scientists a valuable method to move up the value chain and retain relevance in the future of work.
You could also read:
By Aditi Bhat
By Arijit Banerjee
By Aditi Bhat
Request a Call Back
The Reskilling Imperative: Retraining Workers for the Age of Automation
Emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), deep...
Manipal ProLearn Launches its Cybersecurity Program in Partnership with HackerU
There’s good news for cybersecurity enthusiasts in the country. Manipal ProLearn has launched a new...
New product sales: Three steps to create a winning culture
New products account for a substantial chunk (27%) of sales across industries. Selling new products...
Artificial Intelligence:The Digital Marketers New BFF
As companies are looking to increase their budget on marketing, they are also looking for newer...
Continuous Learning Leads to Continuous Success!
Where do formal education stop, and professional career begin? For many of us, it ends right after...
5 Cyber Security Jobs which are Taking the IT Sector by Storm
In an era where information technology has deeply penetrated a multitude of organizations across...More Info
How to Build Teams That Drive Extraordinary Results?
Teams are the backbone of modern organizations - project teams, executive teams, marketing...
Here's the Top Ten Career Paths to be Considered in Cyber Security
As digital transformation sweeps the world with next-generation technologies, Cyber Security has...
Top Five Skills Necessary to Set Up a Stellar Career in Cyber Security
The mind-boggling pace at which technologies continue to evolve has opened a whole new front of...
How to Get Hands-On Experience in Cyber Security
This is the best time to take up a career in Cyber Security! The ever-growing market for experts in...