In talks with Krishnamurthy Siddayya I Accredian Spotlight

With over 12 years of experience in diverse industries like banking, finance, real estate, etc, Krishnamurthy Siddayya now wants to give his career a sharp turn towards Data Science. So to upskill and master data science and machine learning concepts he enrolled for the Python data science course known as the Certificate in Data Science Foundation (CDF) program at Accredian. 

In this interview, let’s see what is his take on the impact of data science on the job market and how his experience has been at Accredian.  

Question 1: Which program & batch are you part of at Accredian & tell us more about your current work profile?

Krishnamurthy: I am part of the Certificate in Data Science Foundation (CDF) program, August 2020 batch. I’m currently not working with any company, and I would like to change my career in the data science field and upgrade myself in ML in the future.

Question 2: Walk us through your career journey & what got you interested in Data Science & Machine Learning?

Krishnamurthy: Overall, I have 12 plus years of experience in the BPO industry. I started my career with Affiliated Computer Services India Private Limited, Bengaluru, where I worked as a transaction processor from October 2005 to January 2007. I have worked in multiple domains like healthcare, finance, administration, etc. 

Later on, I got an opportunity to work with the Global BPO Services, Bengaluru, and I worked there as an associate team member from August 2008 to November 2011. After that, I joined Fidelity National Financial (FNF) and worked as a senior analyst in the process team for over eight years.

In FNF, I used to do research on legal owners of the property to ensure there is no discrepancy regarding loans, clear titles, etc. I am a part of the US mortgage and insurance process dealing with homeowners and condominium insurance policies, verifying clients’ KYC documentation, and validating policy details. 

As far as data science is concerned it is one of best jobs of the 21st century. It’s high in demand, but sadly, there are not many data scientists in the market. Data Science is widely used in diverse sectors like banking, healthcare, e-commerce, social media, etc. It helps businesses make smarter decisions. Since I have exposure in the medical, real estate and banking industries, I can upskill in Data Science through Accredian’s Python data science course and utilize my experience to build a good DS model.

Question 3: What are some initial challenges when you got started on your Data Science journey, and how did you overcome them?

Krishnamurthy: Since I am from a non-technical background, I was not aware of coding and so it was challenging for me at the beginning of the Python data science course. But I have spent my time practicing the basics of Python and am able to work on related projects now. Also, interpretation of data was challenging initially, but as I practiced it more, I analyzed data well in the projects that were given to me and was even able to perform critical analysis.

Question 4: Who is your favorite faculty at Accredian, and what did you learn from him the Most?

Krishnamurthy: My favorite faculty at Accredian is Suchit. He helped us build a GitHub profile. His recorded videos on Python and statistics in the Starter Kit were really helpful, especially for beginners. Nikhil has also helped us in the resume workshop, where he taught us about building a professional resume.

Question 5: What is the goal of Data Science?

Krishnamurthy: The goal of data science is to construct the means for extracting business-focused insights from data. This requires an understanding of how value and information flow in a business and how to use that understanding to identify business opportunities.

Question 6: In your view, how has Data Science evolved in the last few years?

Krishnamurthy: As far as I know, data science started evolving in 1962 when John Tukey demonstrated it as data analysis. Later, there were many transformations, where the concepts and principles of statistics were used for data analysis with computing and in 1974. 

Peter proposed the term data science in recent times. The expansion of statistics into the technical areas made data science more popular, incorporating computer science, mathematics, statistics, information visualization, graphic design, complex system, communications, and business. It is widely used to make intricate work simpler through machine learning and artificial intelligence. And that’s why, right now, Python data science course is a necessity. 

Question 7: What are the current trends in Data Science that you are most excited about?

Krishnamurthy: The current trend lies in businesses’ implementation of data science, machine learning, and artificial intelligence to have miraculous achievements. ML and AI have been witnessing rapid growth, and the combination is actually helping businesses to look for a quick, cost-efficient, and innovative way to gain advantages. Data and analytics combined with artificial intelligence technologies offer a boost to predicting business continuity. 

Question 8: Which are some of the blogs that you follow?

Krishnamurthy: During and even after my Python Data Science Course at Accredian, I follow blogs on Medium, Kaggle, GitHub, Towards Data Science, and KDnuggets. I have subscribed to several YouTube channels on Data Science and listen to Stat Quest recordings.  

Question 9: What is your advice to anyone wanting to start a career in Data Science?

Krishnamurthy: I would really advise all professionals to learn data science irrespective of their industry or job responsibilities via self-study or formal courses like the Python data science course at Accredian. Data Science applications are intercepting all industries across the globe right now and it will be useful for anyone who wants to upskill and have a better career. 

This was a conversation with one of our CDF students – Krishnamurthy Siddayya. 

To discover more interesting student interviews, check out Accredian Spotlight.

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