Why Choose Data Science As Your Career?

The importance of data science cannot be overemphasized more than now. It is merely the study of date after recording, analyzing, and storing it. The quest is to extract all useful information on it. Data science has sprung a new field of analysts called data scientists, who carry out the same activity, but they lend a new angle to it. They improve the quality of the data and try to benefit the company with such enriched new data. As mentioned before, it has revolutionized technology, and many are flocking towards this profession.

On the other hand, all that glitters is not gold, so we attempt here to weigh the merits and demerits of this job, which has been hailed as the “sexiest job of the current century.”

The pros of being a Data Scientist:

1. It’s ‘The’ job in Demand.

It has become the fastest ever-growing employment opportunity and would cater to something more than 11 lakhs job seekers by the end of the year 2026. Through this, we can be sure that data science is here to stay.

2. Skill is a must!

To become a data scientist, one must have the requisite skill set. Not everyone can qualify, and thus the Demand would be maintained at a high price, which would drive the sector upstream.

3. A lucrative Job:

Since the Demand is maintained at a high, the salaries and perquisites that go along with it are also equally high. The highest salary (average)drawn as of now, is more than $116 K per annum, making it quite a lucrative offer.

 

4. Data science is all-encompassing:

Data science is not confined to one area of study or application. It is the entire gamut. The most popular industries are a part of the clientele who require their services. For example, E-commerce and banking.

 

5. Who needs who?

Without a data scientist, the data collected is a waste. In other words, there might be a few useful analyses made, but this would not be in the same league as a data Scientist.

 

6. Data scientist- A social standing!

A data scientist would be regarded as a position in the company, as a part of the top echelon. This, in turn, would translate into a person oh high social standing in the society where he resides.

7. Not a mundane Job:

Since data scientists have aided businesses to reach a new high, and given the fact that it is an active job, repetition at work is almost ruled out. This gets rid of the boredom, which other jobs have in them.

8. Smarter, Brighter:

By using the analysis of data, the interaction between humans and computers has grown stronger, to deliver intelligent products that would suit the client’s needs.

9. A lifesaver:

The primary beneficiary of data science has been the health care system. Through the accurate interpretation of medical data, it has become far more comfortable to detect a tumor or their ailments at the early stages itself.

10. Best of both worlds:

The study of data science makes the analyst sharper in troubleshooting. It also involves IT management, and thus, knowledge of both worlds is integrated as one.

 

These are the various merits or advantages that support the cause of why one should choose the career of a data scientist.

Now let us examine the various demerits or ‘Cons” of this.

Cons of choosing Data Science as a career:

1. “Fitting in the problem.”

The problem, theoretically, that is, is that Data science does not have a definition nor a perfect meaning since many consider it as an extension of Statistics only, and others argue that it is the fourth paradigm of science. Therefore a data scientist would assume the role of whatever hic company wants him too, and the choice might not be his.

2. Master of all three:

Data science is a mix of computer science, Mathematics, and Statistics. One has to be a master of all three, to separate the data in its proper perspective, and them analyze it. For this, he has to be an expert on all three fields mentioned above. This is where the skill gap emerges, and the data scientist has to keep educating himself in all areas, to remain an expert, which is next to impossibility and he has to seek Online assignment help.

3. Lack Of domain Knowledge:

The best way to illustrate this shortcoming is via an example. In the health care industry, specific medical knowledge is required, along with the ability to process data. But the data scientist would have limited ability to interpret complex medical data. Therefore, the emphasis on domain knowledge is a must, and all data scientists, cannot equip themselves with it and would require assignment help.

4. Data analysis VS Unexpected results:

When the data scientist analyses the data, he needs to make predictions that are close to accuracy. If the data is not sufficient or if the information is erroneous, the actual result would throw up a few unexpected results. This would render the whole process useless.

5. Infringement dangers:

Data is the starting point of any analysis. Decisions are taken based on these data. The information is sacrosanct to each company or institution. The information is generally well protected, but if there happens to be a theft of such material or leak, the whole process has to be shut down, there is also a legal issue in this, as data relating to personal problems, may go into wrong hands.

Conclusion:

There is no doubt from the above arguments that disadvantages do exist in the field of Data Science. Even though the Pros outweigh the Cons, strict monitoring of the process, security, and ever-expanding knowledge is the order of the day. It involves continuous education, and one may become obsolete if this is not done. Therefore the choice of pursuing this field has to analyze by the incumbent primarily.

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