Presenting to you the INSAID Spotlight Budding Data Science Leader interview series. This is a series of interviews of budding data science leaders, enrolled with INSAID in different courses. These students coming from diverse backgrounds and even different fields, have rich experience in their own domains. They have interesting views to share with the world, their experience in the industry, what brought them to the field of data science and many other such interesting aspects. These interviews will enrich the readers about the insights, trends and many other related points.
In a recent conversation, we spoke to Sharad Dubey who is enrolled in the CDF program at INSAID.
Student Name: Sharad Dubey
Current Organization: Heuristech Labs Pvt Ltd, Noida
Total Experience: 4.9 years
Batch: Certificate Course in Data Science Foundation (CDF) November 2018
Ankita: Sharad, if you could please walk me through your career journey; what is your educational background, your experience and the current capacity you are working in?
Sharad: I did my B.tech. in 2012 in Electronics and Communication and started my career as a System Engineer with Roboflux Technologies. Currently, I am working as a Team Leader (Machine Learning) in Heuristech Labs Pvt Ltd, where I am involved in the analytics domain. Apart from this, I am actively searching for a suitable role in Data Science.
Ankita: What got you interested in the field of Data Science? What built your interest in this field?
Sharad: I don’t come from a programming background. It was just two or three years ago that I started learning C and Java programming language. But when I got more acquainted in this space, I learnt that Python is the more programmer-friendly language; people who are new to the world of programming can easily understand it.
This is why I also started learning Python as it is a very interesting language. After working for 6 months in Python, I came to terms with machine learning and data analytics. Getting inquisitive about these new terms, I also watched a lot of YouTube videos to know more about them.
As a result, I came to know that mathematics and statistics form the base of this newfound sphere. Since maths was my favorite subject since my school days and the B.Tech. time, I then decided to get into machine learning and opted for INSAID.
Ankita: Right. My next question to you is- what all tools and packages have you mastered in Data Science and Machine Learning?
Sharad: I have just worked on the Tableau and Qliksense tools. Actually, more part of my work is on Tableau. I have also done my work on Python packages like Matplotlib and Seaborn library; just the basic ones. Also, almost all the organizations working in the field of data analytics are using Qlikview and Qliksense.
Ankita: I understand that you have worked on the basic ones. But you have a wider working scope, as far as all these tools and packages are concerned. Now, if you could tell me about any machine learning algorithm that you have studied and is your favorite?
Sharad: Yes, I have worked on many machine learning algorithms like Linear Regression, Decision Tree, Random Forest, KNN and others; as a matter of fact, I have worked on almost all the machine learning algorithms.
Ankita: Which one is your favorite?
Sharad: Ensemble Learning and Random forest are some of my favorites. The reason is that these are very useful for businesses and have an amazing accuracy.
Ankita: Great! Sharad, now could you tell me what according to you is the goal of Data Science?
Sharad: With the manifold increase in data, the goal and purpose of Data Science has also widened. It is not just limited to classification of data but has moved on to structuring the data, managing and processing it in a way to produce useful insights for the business is the key goal of Data Science.
Ankita: True! So, are there any blogs that you read?
Sharad: Yes! I read blogs on towardsdatascience and medium websites.
Ankita: Sharad, my next question to you would be- at INSAID, students are encouraged to maintain their GitHub profiles. So, I believe you also have a GitHub profile. How do you think it will help you in the future?
Sharad: Yes, I have an active and updated GitHub and LinkedIn profiles. Having your projects on your computer will not be of any use. Updating it on your GitHub profile will be its best use. In this way, the companies wanting to hire you will also know about the work you have done.
Ankita: So, crafting a great Data Science resume is a critical part of getting shortlisted for Data Science roles. Tell us some ways in which you have improved your resume as a part of Data Science Career Launchpad.
Sharad: Other than the usual and important things like career objective, experience etc., mentioning other equally important things like Tools and packaged worked on; languages learned etc. will definitely help you get shortlisted in the interviews.
Ankita: INSAID’s mission is to groom Data Leaders of tomorrow; what do you understand by data leaders? And how are they different from Data Scientists?
Sharad: Data Leaders are the ones like me who have led a team of Data Scientists; Data Scientists are the people who are working under the guidance of these Data Leaders.
Ankita: Sharad, my last question to you would be- what will be your advice to the freshers who are about to start their career in Data Science or actually want to enter in this field?
Sharad: There will always be people from different fields coming into this field of Data Science and machine learning. They might think it is difficult but actually it is not.
Always being hungry to learn more and staying updated is the key to succeed in the interesting field of Data Science. Having shallow knowledge won’t help much; your guide and friend will be the deep knowledge of the basics related to this field.
Ankita: Any feedback for us at INSAID?
Sharad: Everything is good. Apart from all that is done in the various sessions, I would want INSAID to personally guide me in my career path; what do I need to do and what all things I should not, while giving interviews.
Ankita: This brings me to the end of the interview. It was nice talking to you, Sharad. Thanks a lot for your time.