This data analyst says you don’t need a dime to start a career in analytics

Data science professionals win the biggest paychecks, but these professionals have also invested heavily in their education to modernize their careers in line with industry demands. But do we know how they got into this field and above all, what was their learning path to become a data scientist?

Analytics India Magazine has launched a new column – ‘My Journey in Data Science’, where we feature seasoned data science professionals and their side of the story.

This week we contacted Pravat Ranjan Jena, senior data analyst and BI at Dell. Jena has over 6 years of experience in the data science field. Over the years he has worked on several successful projects and his recommendations on LinkedIn are undoubtedly a testament to his success.

A graduate of ITER – Siksha ‘O’ Anusandhan, Bhubaneswar, Jena has always been passionate about data. While her fellow students weren’t aware of the popularity of the data, Jena was already exploring space early on.

“There was a time when many of my college friends didn’t know the importance of data. They even laughed at me thinking that I was wasting my time doing data all the time. I’m not bragging about it, but today it’s been over 6 years and I’m in a much better position than most of them, ”said Jena.

When asked how he managed to land his first job, Jena said he made the most of an opportunity. There was an interview at Intel Security (McAfee) and Jena managed to land the interview and land the job. He worked with companies like Oracle and IHS Markit as a data analyst – he worked on ddata management, data mapping and cleaning of mass records and data enrichment.

“Data science is amazing. You never get bored – every day seems to be exciting. I personally think that this field teaches you on a daily basis. The learning never stops, ”Jena said.

The learning phase

Speaking of the learning phase, Jena has never taken a data science course. Dell data analyst believes that if there is anything you want to learn, you can always do it without spending a dime on class.

“There is a tremendous amount of free content available on the Internet. You just need to know how to get the most out of it, ”Jena said.

Even though Jena believes that the internet is full of resources for learning on a lot of topics, he also believes that there are many channels, influencers, and YouTubers that are misleading data science aspirants and newbies. Jena’s advice is to stick with authentic learning resources and not to follow scammers or fake influencers who position themselves as experts in the field.

Jena’s entry into data science was purely on the job. “When I got my first job, I put a lot of effort on my part, so it became easy for me to learn and work at the same time,” Jena said. “When you work for a company, it’s not just the salary you get, but whether you accept it or not, you learn. You just need to have the enthusiasm to think of everything as an apprenticeship.

Here’s how you deal with rejection and improving skills

When asked how he deals with rejection, Jena shares that he has always been positive about everything in life. According to him, a rejection does not mean that you do not have the required skills, it means that he is not suited for the job. So instead of complaining about the rejection, take the next step and try again.

On improving skills, Jena shared her experience:

“I once went to an interview where the interviewer asked me if I had experience with databases. I said that I have been working with SQL Database for a while. However, the interviewer said he was looking for someone who has experience with MongoDB.

Over time things change, whether it’s skills, tools, or anything else. So what you need to do is keep perfecting and learning new tools. Don’t limit yourself to the tools you use in your current job. Explore the area; see what’s going on in the industry.

Jena’s advice to all aspiring data science professionals

If you are a novice, don’t jump straight into learning the critical aspects of machine learning or artificial intelligence. First of all, try to know the industry – knowledge of the field is really important. You have to understand the trends in the industry. Later, you can move on to learning programming and databases.

Jena reveals that you don’t have to spend a lot of money on class. He believes that one can certainly make a great career in data science by using open and free sources available on the Internet. Don’t confuse tools and concepts either. Learn the right way.

“Don’t be tempted by other data scientists using high-end tools and solving complex problems. Everything takes time, even the best data scientists started from a basic level – get the fundamentals solid Start with the basics like SQL, Table, MS Excel etc. then move on to high level concepts ”, Jena said in conclusion.

Sean N. Ayres