One of the most exciting jobs and in demand jobs around the globe: Data Scientist

Analysis of Data has become one of the vital focuses of companies presently. It is not something new, it has been around since a long time, it just has sprung into limelight. With the current rate of expansion of businesses and humongous amount of users on the internet, it has become vital for companies to analyze data of their consumers in order to gain the competitive edge.

Who are Data Scientists?

Data Scientists are present day superheroes. They are good in programming, are trend-spotters and are also amazing statisticians. Analyzing vital changes within the business cycle, understanding consumer behavior, predicting future outcomes. Probably in the future, Data Scientists will become synonymous with fortune tellers.

Why is there a demand for data scientists?

Data has always existed. Back in the day, we did not have machines that could store and compute large amounts of data. So we focused on building machines and technologies that can actually store and compute huge amounts of data. We made our machines smaller and faster, but failed to train our professionals at the same pace. This slowly created a gap between the technological progress and professionals involved in it. And here they are, Data Scientists. It’s a simple equation of supply and demand when you consider the career path of Data Scientist. Presently, there is huge supply of data to be interpreted, but there is a lack of professionals who can compute this data correctly. This has left a huge gap for proficient candidates to learn the relevant skills and fill this gap.

The market right now is looking for competent decision makers.

What are the skills required to become a Data Scientist?

Statistics: A Data Scientist is expected to be a very competent statistician and also a sound computer engineer. The perfect Data Scientist is expected to have the right balance between numbers and applying them in the technologies.

A Data Scientist is expected to be a very competent statistician and also a sound computer engineer. The perfect Data Scientist is expected to have the right balance between numbers and applying them in the technologies. Machine Learning: Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data. This will essentially help you understand consumer behaviour and how to incorporate better interactive results in which the machine communicates.

Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data. This will essentially help you understand consumer behaviour and how to incorporate better interactive results in which the machine communicates. Predictive Analysis, Data Munging, Visualization, and Reporting: Conversion of raw data into forms that are easy to study, analyze and visualize is called Data Munging. Visually appealing data makes a great representation of the data along adding a streamlined aspect towards understanding the report. Tableau is one of the popular technologies used for data representation.

Conversion of raw data into forms that are easy to study, analyze and visualize is called Data Munging. Visually appealing data makes a great representation of the data along adding a streamlined aspect towards understanding the report. Tableau is one of the popular technologies used for data representation. Coding in Python and R: Major part of your job would be finding data and analyzing them. But unless you understand what the data is about, there is no use of that data. This is where knowledge of programming languages comes into play. R & Python are some trending languages in this career path.

Major part of your job would be finding data and analyzing them. But unless you understand what the data is about, there is no use of that data. This is where knowledge of programming languages comes into play. R & Python are some trending languages in this career path. Learn to work on databases like MongoDB, the most popular NoSQL database: Work on Databases and understand how to analyze and build predictive models based on the data.. MongoDB was currently voted to be the most trending database data scientists work on.

Work on Databases and understand how to analyze and build predictive models based on the data.. MongoDB was currently voted to be the most trending database data scientists work on. Develop Communication Skills and Communicate Effectively

After effectively honing your technical skills, it is also important to improve your communication skills. It is your analysis, your hard-work, your report, your model. Effective communicative skills convey the correct message you want to convey and also help understand your analysis correct.

What would be the benefit of becoming a Data Scientist?

First you will be doing businesses a big favour. As mentioned before, there is a lack of good scientists and plenty of data to work on. Making a switch into this career path will be highly progressive and fruitful as future scope of a data scientist is quite bright. Companies are actually hunting for good data scientists and in turn offering lucrative salary packages. As a fresher, a Data Scientist can easily earn 5–8 LPA which can turn into double figures within a couple years of experience.

How can you become a Data Scientist?

At edWisor, we incorporate all the above mentioned aspects in our career path as a Data Scientist. We aim to hone our candidates with exposure to the latest technologies used in the industry along with real time projects to provide the job-like experience in order to ensure high productivity in our candidates. Most of the academic institutions do not provide exposure to these relevant technologies making learning these technologies a difficult task.

As an online skilling platform, edWisor is easily accessible to aspiring data scientists and with our module being self-paced, even professionals willing to learn can become data scientists while still being employed.

Analysis of data is slowly becoming the need for the future, and we hope to fill the gap with training candidates proficiently.