Why One should pursue a career in Data Science
Data science or the stream that deals with the exploration, analysis, modelling, and generation of meaningful information from data is the buzz word across industries. Organisations are increasingly acknowledging that they are sitting on treasure troves of data. The immediacy to analyse this data and generate ROI is evident.
But these organisations need talented data scientists, data engineers, and AI engineers to turn that potential into real opportunities. On the other hand, data scientists can learn a lot and use their skills by working at big companies that have the infrastructure to build AI factories that turn data into real-world success.
Shortage of Skilled Resources
A study by McKinsey Global Institute reveals that the US will face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data by 2018. The demand is particularly acute in India, where the technologies and tools now exist, but not skilled users. “There are two types of talent deficits: Data Scientists, who can perform analytics and analytics consultant, who can understand and use data,” says co-founder and CEO of Fractal Analytics, Srikanth Velamakanni. “The talent supply for these job titles, especially Data Scientists is extremely scarce, and the demand is enormous.
Exploiting the Power of Data
One of the driving factors that is increasing demand for data scientists is the growing power to gather data from the physical world. We can see this in a wide range of areas that digitisation had not penetrated before.
The trend of connecting and digitizing industrial environments will grow with the advent and expansion of 5G networks that can provide robust connectivity in factory floors. 5G is also helpful for bringing information back to the operators and supporting engineers; data that they could only access from their work PC can now be easily streamed to the shop floor.
We can see similar trends in many sectors. For instance, in healthcare from personal gear to hospital equipment, there’s more connectivity and data-collection capability than ever before that creates unprecedented opportunities for applications of data science.
An Impressive Pay scale
A Data Scientist’s job is among the top-paying in the industry right now. As per GlassDoor, the national average salary for a data scientist or analyst tops over US$62,000. In India, the experience strongly influences the pay. Those with the right skillset earn as high as 19 LPA.
Plethora of Roles
Wherein ‘Data Science jobs’ is an overreaching term, within its larger meaning, many other sub-roles are available. Roles like Data Scientist, Data Architect, Data Analyst, Business Analyst, BI Engineer, Database Administrator, Data-and Analytics Manager are in high demand.
Data Science IRL
As an experienced data scientist will tell you, there’s a big difference between doing academic and research work in universities and educational institutions are working on real-world projects.
You are typically training and testing your machine learning models on data sets that have been cleaned and preprocessed for educational and research purposes. Your input is data and output of precision and accuracy metrics. The focus in these ecosystems is to learn and to push the limits of science. Academic research in ML creates the backbone of a lot of the applications we use every day.
But when it comes to real-world applications, tools that people will use in their everyday lives, different challenges come up. Data can be scarce, hard to gather, fragmented, or non-existent. A Data scientist needs the help of skilled database engineers to create consolidated stores of data to train and test ML models.