Mubashar Awan: Navigating the Data Science Landscape

Mubashar is working as a lead AI/ML Engineer at Afiniti, Pakistan. He has 5 years of experience in this field, working previously for FBR and Graana in Pakistan. He has always been passionate about AI, keen to learn about new advancements in it. Mubashar is not just interested in building models, but the engineering level work also excites him; to make models productionalize, so that the end user can benefit.

What got you interested in Data Science?

I got interested in this field because I was fascinated by its ability to predict based on historical data. The idea of taking insights from data and making informed decisions intrigued me from the start. My first experience with this field was interaction with chatbots that could mimic human behavior. Although I was initially unaware of the science behind it, I got curious and eager to explore it further. As I started studying this field, I realized the capabilities this field offers. It has a vast range of techniques and methodologies that can be applied to various industries and domains. 

Another aspect that stands out for me is the dynamic nature of data science. Each project has a unique challenge, requiring a person to think creatively and find innovative solutions. There is no room for repetitive work, each project offers the opportunity to explore new data and work on new models.

Moreover, it’s a multidisciplinary field that includes mathematics, statistics, programming and enables you to have a diverse skill set. Ultimately, my interest in data science is to contribute to this growing field and make data-driven decisions.

What distinguishes your work from that of your contemporaries?

In my opinion, what distinguishes my work from that of my contemporaries is that it allows me to think creatively. It pushes you to think big and try new ideas. It doesn’t have the repetitive nature of work, with each new project you’re working on new problems and exploring new domains. Because of the ability to work with real data, It allows you to learn about different domains.

What has been the most surprising insight you have found in your career as a data scientist?

From my experience, one thing which could be beneficial for the newcomers in this field is that whenever a new person tries to learn about this field, he/she tries to jump into deep learning or transformers these days. But from my experience, I have seen that simpler solutions work most of the time. It is always a good practice to try base models, if they can solve the problem as they are easier to explain to the stakeholders too. But if problems require to work on deep models, then one can definitely give it a go.

What would be your advice to young and aspiring data science students who are trying to navigate in the world of data science?

My advice to young students who are passionate about this field is to be persistent. It takes time to understand it, and with rapidly evolving it is also important to keep yourself updated with recent advancements.

What does the future of Big Data look like?

With the amount of data growing continuously, the future of big data is bright. The demand for data scientists will continue to increase. Different businesses would require data scientists to make sense of their data. 

The security of data would be a big aspect which is a challenge to address. Data will become more and more complex and would require data scientists to have a deeper understanding of techniques.

Picture Credits: Mubashar Awan