Being a Civil Engineer and having extensively worked in projects as a Design Engineer gave me fair exposure to core engineering, and at the same time got me fascinated by the business side. What started as a curious urge to know more turned into passion. My motivation to pursue “Engineering Management,” which offers me best of both worlds and what better place than Purdue University, grew directly from this passion. Engineers today can create wonderful products, and the resources available give us endless possibilities. However, it’s equally important to have a sense of whether our innovations have the ability to address consumer needs, and can aid in solving global issues the world is facing. To achieve a profitable and sustainable business that relies on engineering also demands organization structure, focused goals, and measured efficiency to manage huge chunks of data available for us. This is where engineering management facilitates coordination and innovation between engineering teams and business teams, so both can be aligned in working toward the goals of an organization.

The three most high-demand jobs for MEM grads are Product Management, Data Analytics, and Project/Operations Management/Supply Chain, out of which my interest lies in the Data Science field. Even though I came from a Civil Engineering background, the course curriculum at Purdue served as the best platform to transition into a Data Science platform. Courses like Machine Learning, Database Management Systems, Data Mining, and Business Analytics have helped me transcend my horizons and honed my skillset to a greater extent. In addition to the coursework and its associated academic projects, I found Purdue’s Center for Career Opportunities (CCO) to be an effective resource which helped me in securing a co-op in my area of interest. Purdue’s CCO empowered me with job search strategies, career planning, professional advising, mock interviewing, and more. Making the best use of these resources ultimately helped me become a Data Science Intern at a Fortune 100 insurance firm, where I secured an opportunity to conduct the exploratory data analysis and predictive modelling using various natural language processing techniques. Through this industry co-op, I gained knowledge to conduct data engineering operations on large and heterogeneous volumes of data. Access to these resources gave me confidence to apply theoretical classroom concepts into practice. I spent my co-op building my network, working with industry professionals, and growing my analytical and problem-solving skills.

All these efforts have allowed me to put my best foot forward in the professional world. There is no doubt about how experiential learning at Purdue MEM played a crucial role in pushing my boundaries to explore the world of data science, not to mention the resources that helped me transition from a Civil Engineer to a Data Scientist, thereby making my dream come true.

Boiler Up!