How to Become a Data Scientist in 2019?

Data Scientist is one of the most demanded jobs around the Globe
Analysis of Data has become one of the vital focuses of companies presently. It is not something new, it has been around for a long time, it just has sprung into the 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 a competitive edge.

how to become a data scientist in 2019
how to become a data scientist in 2019

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 a 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.

Data Science & machine learning language
Data Science & machine learning language

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.
  • 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 behavior 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.
  • 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.
  • 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.
  • 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 favor. 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 the 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.

Data scientist salary in India
Data scientist salary in India

Your search ends here! Become a Data Scientist today and earn 5–8 LPA as starting packages!

How can you become a Data Scientist? we incorporate all the above-mentioned aspects of 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 learning platform, people could easily accessible 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.

edWisor

edWisor started in 2015 with a vision to transform the professional career of millions of students and professionals who are struggling achieve their Dream Career. We have created a unique ecosystem with a combination of ed-tech and HR-tech platforms. edWisor provides complete job-skills in technologies as per industry standards required for trending career paths such as Data Scientist, MEAN Stack Developer, etc. At the same time meeting industry demands with a Skill Pool of job-ready, up-skilled and assessed candidates under edWisor eco-system. Thus providing an end to end solution to the skill and employability problem faced by industry and students/professionals. With over 5000+ careers transformed and over 250+ Hiring Partners hiring from edWisor. We are India’s first platform to offer ‘Guaranteed Interviews’.

You may also like...

Leave a Reply