Being a Data Scientist could be rewarding in 2021

by Puja Das

December 19, 2020

Data science or the flow that deals with the exploration, analysis, modeling and generation of meaningful information from data is the buzzword in all industries. Organizations increasingly recognize that they are sitting on treasure troves of data. The immediacy of analyzing this data and generating a return on investment is obvious.

But these organizations 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 in large companies that have the infrastructure to build AI factories that turn data into real successes.

Shortage of qualified resources

McKinsey Global Institute study finds that the United States will face a shortage of around 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data. by 2018. Demand is particularly acute in India, where the technologies and tools now exist, but no skilled users. “There are two types of talent gap: data scientists, who can perform analysis and analytics consultants, who can understand and use data,” says Fractal Analytics co-founder and CEO Srikanth Velamakanni. “The supply of talent for these job titles, especially data scientists, is extremely scarce and the demand is huge.

Harness the power of data

One of the driving factors that increases the demand for data scientists is the growing ability to collect data from the physical world. We can see it in a wide range of areas that digitalization has not entered 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 factories. 5G is also useful for reporting information to operators and support engineers; data which they could only access from their work PC can now be easily transmitted to the workshop.

We can observe similar trends in many sectors. For example, in healthcare, from personal equipment to hospital equipment, there is more connectivity and data collection capacity than ever before, creating unprecedented opportunities for data science applications.

An impressive salary scale

The work of a Data Scientist is currently one of the highest paid in the industry. According to GlassDoor, the national average salary for a data scientist or analyst exceeds $ 62,000. In India, experience strongly influences compensation. Those with the right skills earn up to 19 LPA.

Plethora of roles

Where “data science jobs” is too broad a term, in its broadest sense, there are many other sub-roles available. Roles such as Data Scientist, Data Architect, Data Analyst, Business Analyst, BI Engineer, Database Administrator, Data-and Analytics Manager are in high demand.

IRL Data Science

As an experienced data scientist will tell you, there is a big difference between doing academic and research work in universities and educational institutions working on real world projects.

You typically train and test your machine learning models on data sets that have been cleaned and preprocessed for educational and research purposes. Your input is precision and accuracy metrics data and output. The goal in these ecosystems is to learn and to push the boundaries of science. Academic ML research forms the backbone of many of the applications we use on a daily basis.

But when it comes to real-world applications, tools that people will use in their daily lives, there are different challenges. Data can be scarce, difficult to collect, fragmented or non-existent. A data scientist needs the help of skilled database engineers to create consolidated data stores to train and test ML models.

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Sean N. Ayres