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From Electronics Engineering towards Data Science: Divyanka did it, You can do it too.

You are currently viewing From Electronics Engineering towards Data Science: Divyanka did it, You can do it too.

Data Science being a lucrative forte has managed to engage more and more minds into its ring. Not only it offers a higher professional zing to the millennial aspirants, but the enlarged span of opportunities that it has accumulated till now is also driving the new-gen to take it is a reputed profession. The question arises, Do you need to be from a definite educational background to pursue Data Science. I know this question might be boggling your mind too. But, the happy news is, yes, you can pursue Data science irrespective of your stream. Such is the experience of Divyanka Jain, an Electronics Engineer who later had a successful career transition by being a Data Scientist.

Let’s see how the journey of transition has been for her.

Electronics engineering to Data Science.

Academic Education: Btech; Electronics and Communication Engineering

Previous Job Profile:

Company: Cognizant technology solutions

Profile: Software Engineer

Domain: Python

Experience: 4 years.

Current Job Profile:

Company: Siemens

Profile: Data Scientist

Domain: Analytics.

Career Transformation story

Q1.Good Morning Divyanka, tell me, being an Electronics Engineer what exactly drove you towards Data?

Yes, I have pursued my Engineering in Electronics. During the 4 years journey, it was all about circuits, Mathematics, a little of Programing and coding. But I want to tell you. I was good at Statistics in my school day, and I was a coding enthusiast too.

After Engineering, I follow the same way of choosing to be a Software engineer as most of the Engineers do. But then, after a few years, the workflow became very monotonous for me, as there was a rare chance to grow in that field. And I remember everybody was talking about Big Data. The name itself sounds sophisticated. After a few research, I realized this field actually suits my interest and forte, as it involves analytical, statistical and reasoning skills.

The career graph it provides is very attracting and highly encouraging, and I was expecting to step up to a greater salary hike those days. All these reasons convinced me enough, why I should not waste any more time and should take on this opportunity of being a Data Scientist as soon as possible.

Q2. What a great deal of effort you had to go through to make this transition possible?

Honestly speaking, my previous job profile where my work was mostly based on Python Domain, so it made my journey a bit easier.

This is true that I was completely unknown to Data and its functionalities. I just knew Python would help me reach there. I thought of taking a professional certification which could help bridge my desire and skills. Fortunately, I came across GEEKLURN through a reference, checked their profile, and I found them reliable to help me make my dream true. Believe me, I think it was the best decision I took by taking the Full-stack Data Science Certification from there.

The curriculum is smooth. They make sure the learning is not hampered due to your belongingness from a different field. Anyway, they start from scratch. I just had to follow what they are teaching. They made me use the best of my Python skills. I had data grooming sessions with GEEKLURN mentors. Their career assistance guides helped me rebuilding a perfect career transiting resume. They made me avail of interviews from some really big companies, and I clicked through finally. I would not say it is very easy, but a decent amount of effort will be definitely worth it. 

Q3.What attributes you had to add, into your skill basket, that you did not know before to reach here?

With my previous attributes, it was easy to start with, but not enough to sustain. So I had to learn a lot of skills, but all of the concepts had an easy understanding. I had to brush off a lot ok already known things like Microsoft Excel, Microsoft Acess, SharePoint and SQL Database.

The Data Science concepts were at the front seat, while I was simultaneously learning Statistical Analysis, R, Big data analysis, SQL and Data modelling. I had to gain proficiency in handling Tablue software too. Apart from all these technical stuff, I got myself into more no of analytics and machine learning. While learning with GEEKLURN, I overtook a few live projects and spent time on enhancing my analytical skills more. 

Q4. Are you satisfied with the perks and Hikes after being a Data Scientist?

I had this idea before entering this field. I had insecurities, too, whether I am making the right decision or not. The decision to Transit domain in any professional field is challenging, fearful and risktaking. You don’t know whether your efforts will be worth it at the end of the day, whether you will reach there where you have planned to. Same thoughts were there in my mind too. But Data turned out to be boon for me. Big Data is really big, you know, so as the opportunity and satisfaction that follows. Within a very short span of time, It clicked for me actually.

The workflow is not monotonous. It keeps your liveliness in check, where you have to think and analyse. There is always something new to work on every time. I think if I see four years down the lane, My productivity has increased, am enjoying my work to the core, while filling big money in my pocket (*smirks*). At the end of the day, it was all worth it.

I got a 45% hike straightaway, and its spiking all along. Coming back to your question, yes am very much satisfied with the work, environment, challenges and money, where I feel me putting all my devotion to the work have been fruitful.

Q5. What will be your suggestion to all the aspirant desiring to become data Scientist, but belongs to a different vertical of educational background other than computer science?

See, the first and foremost thing that I would like to tell you is that your desire has no boundaries and cannot be constricted by educational background if you are willing to achieve it. It really does not matter if you are a simple graduate, an Engineering graduate, or an MBA graduate, If you want to get into this field, any way you can.

If you ask me how to check yourself if you really fit into this, I would say, If you have an aptitude towards statistics and Maths, You love coding, then data science is going to be an easy slider for you. Otherwise, if you don’t have an interest in these attributes, I would not say it will be impossible for you to become a data scientist, but it may take you to burn few loads of efforts more to reach the destination. No matter what, your willingness is going to make you a data Scientist no matter what if you really want to.

Thank you, Divyanka, for sharing your success journey with us and pouring us beautiful insights. We wish you all the success in life. All the best.

Thank you so much. Pleasure is all mine.


Monica is a senior marketing executive. Her skillsets consist of digital marketing and strategy, SEO, marketing analysis and more. She also has her expertise in writing various copies, including web, newsletters, e-books, social media, etc. But, it does not stop here. Her love for writing goes as far as doing poetry connecting science and life.

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