Presenting to you the Accredian Spotlight Budding Data Science Leader interview series. This is a series of interviews of budding Data Science leaders, enrolled with Accredian 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 Koteswara Rao who is enrolled in the GCDAI program at Accredian.
Name: Koteswara Rao
Current Organisation: Tectoro Consultancy Pvt. Ltd.
Total Experience: 19 years
Batch: Global Certificate in Data Science & Artificial Intelligence (GCDAI) January 2019
Ankita: Koteswara, could you please brief me about your career journey; your qualifications, experience and the current capacity that you’re working in?
Koteswara: I have a B.Tech in Computer Science and Engineering from Jawaharlal Nehru Technological University, Hyderabad. Currently, I am working as a Senior Technical Consultant in Tectoro Consulting Pvt. Ltd., Hyderabad. My organization is primarily into product development in capital markets, wealth management solutions. As of now, I’m developing a risk analysis system for mutual fund and the client is based in Hong Kong. With this system, the investors can actually analyze the health of their funds. It has been two years in my current capacity.
Before this, I worked in FTD India Pvt Ltd, which is into the e-commerce domain. I was solely responsible for handling their e-commerce platform, from development to support. Prior to that, I worked in United Online Software Development India Pvt Ltd. Both these companies were in Hyderabad. There I developed a good number of products for internet services. I have close to 19 years of experience and have played different roles like Senior Lead, Individual Contributor, Project Lead, Technical Manager and now Senior Technical Consultant. Coming to the technology side, I have a good experience in C++, Java, RDBMS like SQL, my SQL and others. I’m a master in the design and development of the new software.
Ankita: That is a great amount of experience, in terms of the variety of industries and exposure to different technologies. Now, if you could tell me what got you interested in Data Science and Machine Learning?
Koteswara: I would like to mention one thing here that when I was doing my BTech, I had one course in Artificial Intelligence. I was very good in automation and related technologies, after completion of which one actually gets into the field of artificial intelligence. And, this was the only instance, wherein I got an opportunity in this field and after this, I didn’t get an opportunity to spend time in this direction.
But in recent days, machine learning and artificial intelligence actually picked up a very fast track from 2014 or 2015. This was the time when I heard these terms for the first time, but unfortunately, did not get much time to learn them. So now, I wanted to take this as an opportunity to learn these things; how exactly they are being used in the industry and how to contribute from my side. This was the primary reason why I still remember all the concepts I learned.
Ankita: What all tools and packages in Data Science and Machine Learning have you mastered so far?
Koteswara: I have mastered Python, NumPy and Panda packages very well. And later, I started exploring machine learning algorithms- Decision Tree, Linear Regression etc. I would say that I haven’t mastered them and have just started learning them. I wanted to play with even more number of datasets to understand these algorithms thoroughly. But at least I know what they mean and am spending more time to master them all.
Ankita: What is the goal of Data Science?
Koteswara: The goal of Data Science is not only about algorithms or solving some sort of problems in a given project. But it’s something to do with our daily lives too, where we can apply those concepts. So I strongly believe that Data Science is definitely going to help in my career as well as in my regular routine life.
Ankita: Given your rich experience and the hold in various concepts, be it technical or related to project management and team leading, did you face any initial challenges when you got into Data Science and Machine Learning?
Koteswara: I’m mostly in touch with programming and typically spend 50-60% of the time on programming related aspects. So I do spend a good amount of time on code reviews also. So in that way, I did not find any difficulty in coding in Python, or maybe understanding those concepts.
The only issue I faced and am still trying to solve is the time crunch I have due to a big task list with me. I don’t find any time during the weekdays, given my 11 hours of daily work schedule. So, I grab some time on the weekends and study, practice, brush up my concepts and read.
The concept of statistics is new to me but I’m quite adept at probability and permutation and combinations. I’m very good in mathematics too. Just an exception to this can be some typical formulae in statistics, which I practice after the Accredian sessions.
Ankita: How do you think has Data Science evolved over the last few years?
Koteswara: For example, if you talk about mobile, I am in a habit of reading news and e-papers (newspapers) and following a few things on YouTube. These days, I don’t need to search for what to read next or what story to follow next, it will be handy on my mobile. This means Data Science is definitely playing a big role. At the back end, definitely, all these applications are following my interest. And accordingly, they’re actually giving the next article, story or news to read. This is one very big thing.
Now, coming to the business point of it. Every organization is trying to understand the data and aim for some sort of a personalized and targeted product for a set of people. This is based on the interests of a particular group of people. So, all these things are beneficial for both- the customers and the businesses. Organizations will be able to increase their business manifold and at the same time, customers will get what they’re looking for.
This way, it will bring in a lot of efficiency in the process and also a good opportunity for all the companies to manage the supply chain or maybe demand-supply chain; focus only in the areas of high demand and reduce the production in the areas with a lesser demand.
People might be doing this earlier too; may not be with machine learning but definitely by applying statistical concepts. The difference is that the entire process is now much simpler; earlier, people may be spending hours and hours to understand or maybe to conclude something. But now after all these Data Science algorithms, scientists must be spending lesser time in giving different conclusions. I would like to add that going forward, Machine Learning is definitely going to play a very big role in the world’s economy.
Ankita: At Accredian, students are encouraged to maintain high-quality GitHub profiles. Have you also built a GitHub profile? How do you think this will help you?
Koteswara: I do have a basic portfolio but I need to refine it further. I am doing some assignments as of now, which I want to add in my GitHub profile. Earlier, I knew GitHub is there but never used it in the right way. It was only after joining Accredian that I came to know how effectively I can use GitHub to promote myself.
So, definitely, I would say it is going to help. GitHub is sure to become the next big thing like LinkedIn. Because you cannot keep everything in your resume, GitHub is a place to keep your projects and showcase your learning. The recruiters will be able to know, within a few minutes, what I have learned, what I have explored etc. They will get a good understanding about my profile.
Ankita: My next question is- Accredian’s mission is to groom Data Leaders of tomorrow; what do you understand by Data Leaders and how are they different from Data Scientists?
Koteswara: Data Scientists are the persons who will be typically involved more in analyzing the data and coming up with some sort of conclusions about what next. But coming to a Data Leader, I believe, apart from Data Scientist responsibilities, he should have a good idea about his domain and be in a position to lead the things as well as give some direction to the organization in that domain, to excel in it.
Ankita: Yes. What are some of the applications of Data Science and Machine Learning in the industries that you’re excited about?
Koteswara: I would talk especially about the e-commerce and banking domain but yes data science will play a crucial role in every domain. But as of my experience, Data Science will tremendously help the e-commerce companies in predicting customer behavior and to the banking industry in fraud detection. Even in the stock markets, there might be many scams. How to detect these scams and identify them? Data Science will play a good role here too.
Ankita: So now, given you have a very tedious job to do and you have to study also, how do you manage the time between both the things- job and study?
Koteswara: I always wanted to devote at least a few hours to studies, daily. I read one or two articles daily and this is how I’m in touch. But on weekdays, I don’t get much time to complete my assignments because for this task you need at least one or two hours. I manage to complete the before-sessions study tasks that are for 15 minutes or half an hour. I know I have to pace up with the study sessions and grab some more time to make up. I think I will be able to pick up within the next few days.
Ankita: Definitely, you will be moving ahead because you have already made up your mind to do so. What will be your advice to anyone who wants to start a career in Data Science and who is actually a fresher in this field?
Koteswara: For a fresher, I would like to say that brush up your programming skills in the Python language because this way you will not experience any difficulty in exploring the libraries. They need to spend more time exploring the libraries, write more and more assignments and explore different features in all the libraries. These all are feature-rich libraries and have many functions. Whenever I am working on any assignment, I find out some new parameter in the function to fine-tune my output. So, these kind of things will come only when we experiment. They will have to write code, debug it and experiment with different outputs. And coming to the concepts, I hope even a new graduate should be able to understand the concept and they can move forward. According to me, Data Science is relatively easier, even for a fresher. But only one thing is that they may not have the domain knowledge, but definitely they will be able to pick it up on their own.
Ankita: Indeed a great piece of advice. Lastly, I would want you to share your feedback about your journey with Accredian so far; anything that you wish to say about the course or anything else.
Koteswara: Yes. The course is very good. The instructors are solving all the queries of the students and are even encouraging the students to ask questions. Even a single question never goes unanswered; the instructor provides a solution for it, along with a detailed explanation. If the students don’t get in one time, they explain it again and again, until the student has the concept cleared. Everything is going smooth; even after the sessions, we are advised which blogs and books to read to clear a particular concept. Personally, I liked it.
Ankita: Thank you for that generous feedback. This brings me to the end of the interview. Thanks a lot for your time.
Koteswara: Thanks for your time also. Thank you!!
