Education: B.S. in computer science and engineering
Tell us a bit about yourself.
I am a computer science engineer with over 15 years of experience in design and development of various IP-based products for the telecommunications industry. I currently work for Cisco Systems Inc. and have lived in Texas for over 10 years. Apart from my work, I enjoy spending time outdoors, traveling, cycling, running, shopping and having fun with my family.
What initially attracted you to the data science field?
I was looking to learn cutting-edge computer science technology that would have a large scope and at the same time be valuable in my industry. Analytics and IoT (Internet of things) were the buzzwords I naturally came across, and I started exploring the implications of analytics on collected data. I was fascinated at the depth and breadth of subjects covered in data science, including statistical modeling, database security, deep learning and AI. I decided this is what I was waiting for!
Why did you decide to pursue a Master of Science in Data Science?
Big data has become the center of talk in all industry conferences. After spending a few months taking some short-term courses, I felt that a more thorough and systematic syllabus was required to help me understand the field. An amalgamation of subjects, tools, techniques, software and platforms are required to skillfully analyze and process data at a large scale.
I believe it is important to have a strong foundation in data science to build any useful and actionable insights that benefit the end customer. Doing a master’s program was definitely the right choice to stand out in the field.
Why did you choose DataScience@SMU?
The coursework was ideal – it provided me with the required skill sets to become a successful data scientist. I was impressed at how the faculty come from three different schools within SMU to teach their subject of expertise. The constant additions to the curriculum offered in the program, to keep up with the fast-moving industry, is also commendable. Moreover, the online program is very convenient for full-time, working professionals.
Which skills and tools that the program covers do you find most appealing? Why?
The statistics courses start from fundamentals and go deeper into different techniques like regression, classification, clustering and machine learning. This step-by-step process helps you build a strong foundation and then learn the advanced techniques. I was also impressed at the many opportunities to collaborate and work on different projects. It’s amazing to see how people from such varied industries come together in this program.
How are you able to apply what you are learning to your current position?
There are several ideas being discussed within my organization on how to use data to build new features into products that will aid in managing networks, monitoring quality of products, and solving customer problems with simple analytical solutions. With the knowledge I am gaining in this program, I am now able to understand the possibilities of data and work with data science teams to suggest methods and areas of focus to build the new features.
What surprised you most about the online learning environment?
The collaboration with my fellow students and the professors! Each student is from a different background, and collaborating with a team of varied backgrounds brings out the best qualities in each.
What advice do you have for prospective students?
Data science is a game-changer, but the subject is comprehensive and you will need to pick a specific domain and focus on the subjects that matter most to you. Don’t always act on a hunch; be ready to discuss all your thoughts with your peers, professors, student support advisors, etc. The conversations will give you a good insight about the real data world out there, as some students are already working on big data! Network as much as you can to benefit all!