In 20 years of his career, Deepak Saldanha while heading transition and transversal projects noticed that although there was a lot of data available and stored but there were no tools or applications to leverage them. And so, when he got to know about data science, he decided to upskill himself in it and machine learning with Python and enrolled for the Global Certificate in Data Science (GCD) program at Accredian.
In this interview, let’s take a look at how he plans to apply his data science lessons at work 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?
Deepak: I am part of the Global Certificate in Data Science (GCD) program, August 2020 batch. I am currently the Head of Transitions and Transversal Projects at BNP Paribas Security Services. My role here is to guide and mentor my team to manage operation transitions from several overseas service partners into India.
I also manage the setup of operations to service new clients, and lead programs like setting up dual offices, returns during post COVID and implementing initiatives like digital offices while traditionally archiving documents. The range of projects and initiatives are pretty diverse here depending on the needs and objectives at that time.
Question 2: Walk us through your career journey & what got you interested in Data Science & Machine Learning?
Deepak: Having completed my mechanical engineering in 1998, I started working in the production stream, and within a few months, I found the job pretty mundane.
The software industry was gaining momentum, and I too had a strong liking for software development. Hence, I enrolled in a course and got into the software industry thereafter.
After working for almost a decade in C, C++ and Java, I decided to upskill and sharpen my strategic thinking as my job was very technical. I got admission into one of the premier B schools in the UK and worked there, managing strategic programs and consulting organizations helping them devise and deliver strategy.
I did that for a couple of years, and thereafter relocated back to India in 2011, I got a job to set up the projects and management support division for BNP Paribas security services. And since then I have managed and delivered several successful programs.
While overseeing the management support team a few years ago, I realized that we held a lot of data from various departments. We were churning out loads of semis. But we were really struggling to leverage this data to develop insights and add value to the organization.
I also simultaneously happened to be leading a data service program for a strategic line from a business perspective and got to hear the popular data science jargon from colleagues who were developing this application.
That’s when I decided to get back to the drawing board and enrolled in a data science course to better understand the terminologies and also to learn how I could leverage data science and machine learning with Python to add value to my organization and clients.
Question 3: What all tools and packages in Data Science & Machine Learning have you mastered in your Data Science & AI program at Accredian so far?
Deepak: I have commenced the GCD course around August end and I’ve completed the basics of machine learning with Python and EDA with various libraries like NumPy, Pandas, Matplotlib and Seaborn.
Although I really don’t think I can call myself a master yet, I plan to take my knowledge to the next level by enrolling for some competitions on Kaggle. I also read a lot of blogs to keep myself updated and perhaps someday I might start my own blog on data science.
Question 4: What were some of the initial challenges when you got started on your Data Science journey and how did you overcome it?
Deepak: I really struggled getting back to programming after being in no touch with it for around 11 years. I was quite averse to opening the Jupyter Notebook. And, being a part of senior management, I was not keen to get back to programming after having worked for over 20 years.
However, after a few weeks, I realized that whatever I read was not getting registered in my mind as I had not practiced. After some introspection, it dawned on me that programming would not be very hard for me, as I still remembered my concepts pretty well. So, I started practicing concepts of data science and machine learning with Python.
So I made up my mind to devote at least an hour after work daily to practice in the Jupyter Notebook. I reminded myself that programming was just a means to an end, I could still leverage my strategic thinking to solve problems and programming was just a tool to help me reach this objective.
Question 5: Who is your favorite faculty at Accredian and what did you learn from him the Most?
Deepak: I have so far completed machine learning with Python and EDA. Deepesh was our tutor. What I learned from Deepesh is that data science is hard at first, but you gain confidence once you practice, else all would seem like Greek. Also, he taught me that you need not mug up the syntax of functions as there are too many. But, you need to be aware of their existing functionalities and you could always look them up online. And, even though you are professional, learning would be a continuous journey in the data science field.
Question 6: What is the goal of Data Science?
Deepak: As most of the current generation is technology savvy, for example, getting online to carry out tasks, using apps sharing opinions and concerns through social media, there is a lot of data generated everywhere. It’s ubiquitous, but is of immense value.
The goal of data science is to leverage insights from this data, create opportunities of business value to generate profits, or simply enhance customer support and customer experience quality. It could even be used to develop new innovative products that improve and enhance the quality of life or create new paradigms for products and services.
Question 7: What are the current trends in Data Science that you are most excited about?
Deepak: I am most excited about the use of predictive analytics to eliminate risks and further advancements in data science, as a whole, that would enhance the quality of life. I am also curious about the advancements in IoT, automotive cars, and smart cities.
Question 8: What is your advice to anyone wanting to start a career in Data Science?
Deepak: My advice to anyone aspiring to start a career in data science is to enroll in a structured data science course where you will be taught machine learning with Python. That way you will have some sense of direction. There’s plenty to learn out there.
It’s easy to get lost with so much detail available online. Of course you cannot self study everything. You need to get into the habit of reading a lot to understand new features and functionality.
Also, a lot of practice is required so that your knowledge could be cemented. Remember, you never learn until you get stuck. You also need to sharpen your programming and statistics skills and leverage on your dominant domain knowledge.
Work on a lot of projects from various industries or the industry you are looking to get into. And don’t forget to showcase them on your GitHub profile.
This was a conversation with one of our GCD students – Deepak Saldanha.
If you want to read more interesting student interviews, check out Accredian Spotlight.
