Academic Excellence is not all it takes to be a Data Scientist
Data Science was a term coined by Professor Cleveland in the year 2001. It was the year when Facebook was not even conceived. Kolkata was still known as Calcutta. In addition, the United States witnessed the biggest terrorist attacks in form of the 09/11 incident.
No one would have imagined that this skill would one day become the most sought-after profession.
Why do you want to be a data scientist? Yes, the money is good, probably the best in the industry, but what are the skills to become a data scientist? Read this article to find out the most important factors to remember for becoming a data scientist[1].
The article will be covering up the following topics:
The pros and cons of being a Data Scientist
What does it take to be a Data Scientist?
What types of skills the young professionals have to be a Data Scientist?
What are the monetary benefits of being a Data Scientist?
The Pros and Cons
The future belongs to the assessment of Big Data and database analysis. There are so many exciting opportunities and arenas where the scientist can work. A Data Scientist has to be a master of mathematics and statistics. The scientist takes account of these models and converts it into actionable insights, which can include customer retention and finding new business opportunities. This immense amount of job and unprecedented growth in the industry ensure that there is hardly any dull moment in this profession. This is considered as a disadvantage since the margin for error of the profession is very small.
What does it take to be a Data Scientist?
From an academic perspective, a data scientist is a person having impeccable records and in-depth understanding of calculus and advanced mathematics. Besides this, the profession requires knowledge of programming languages like Hive, SQL, and R, which are used for analysis, and building database models.
There are a few other programming languages, and their usage depends primarily on the organization as well as the skills of the scientists[2].
However, other than the aforementioned skills, a Data Scientist is expected to have decent communication skills, analytical skills, and impeccable ability to communicate with others. Testing hypothesis and data processing could be improved with practice and perseverance. However, the creation of data visualization and storyboarding is an integral part of the professional skills required for this job.
Young professionals and skills development
The unprecedented growth in the demand for Data Scientists in the US market, as well as, the exponential rise in the salaries offered to these professionals, has ensured that the profession attracts the attention of young professionals.
The young professionals should, however understand that the people having strong technical background and strong intuition about data become the best scientists. As described earlier, the role of programming and software is high in this area, but at the same time, the data scientist should be good in communication so that the outcomes could be explained to various entities.
It is highly recommended that the young students and professionals participate in hackathons or offer to help a local start-up by tackling a data problem they have. Even though it would not pay them any financial rewards, still it will give them the exposure, which no courses or classrooms can develop.
The Monetary Benefits
What about the money, honey?
There is a lot of money. Much more than any other profession now. Considering the following chart that shows the demand for the professionals in the US:
The growth trend could be considered as nothing short of phenomenal, if not ridiculous. The total expected demand for Data Scientists is expected to be 50–60% greater than the supply by 2018, thereby making it one of the most exciting career choices.
And yes, the money. It is there. The median salary is close to $118,000 (2015 figures) and in the future, due to the gap in demand and supply, the average salary is expected to rise even further. As illustrated before, it purely depends on the traits like communication and analytical skills of the scientists[3].
Conclusion
Data Scientist as a profession is in evolution stage.
“A data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician.”
The overall roles and responsibilities of a data scientist include conducting undirected research and answering the open-ended industry questions. The job also includes employment of sophisticated analytics programs and machine learning. It is implied that a Data Scientist has impeccable academic credentials having mastery in math, statistics, and computer science. Knowledge of programming languages only add up to the skill set, but mastery is something a prospective data scientist should be looking forward at. Besides this, having communication and analytical skills help a professional in getting the best jobs available in the industry, and earning the biggest packages.
Let us start the conversation on what it takes to be a Data Scientist. Write your outlook in the comments section.