Jhanani Ramesh has been a data scientist at Integra LifeSciences since 2019. Her prior roles include Data Analyst, and Graduate Teaching Assistant, both at Rutgers University. Jhanani holds a Bachelor’s in Electronics and Communication Engineering (ECE) from Anna University in Tamil Nadu, and a Master of Business and Science, Data Analytics from Rutgers.
In our latest post, Jhanani reflects on the educational highlights that equipped her to excel in her current role of data scientist. Jhanani explains how her engineering background strengthened her maths skills and problem-solving abilities, while studying for the MBS program at Rutgers gave her a strong understanding of both business and technical aspects.
During her studies, Jhanani participated in various practical externships. These externships were crucial for helping her learn the importance of translating technical metrics into actionable insights for business users:
I, Jhanani Ramesh, grew up in Chennai, India, and my journey has taken me across the world and into the field of data science. From an early age, I have always been inclined towards mathematics and the latest technologies. This passion guided my academic journey, leading me to pursue a Bachelor’s in Electronics and Communication Engineering (ECE) from Anna University in Tamil Nadu, India. I relished the challenges and complexities that came with this field, and it deepened my curiosity about how technology could be harnessed to solve real-world problems.
My ambitions led me to explore opportunities in higher education, where I could blend technical expertise with business acumen. This search wasn’t a solo journey; my parents played a crucial role in helping me research various programs, tirelessly combing through options to find the best fit for my goals. Together, we discovered the Rutgers Master of Business and Science (MBS) program, a unique combination of an MBA and MS, which was exactly what I was looking for. The high reputation and innovative curriculum of the program made it the perfect choice to fulfil my dreams. The excitement of being accepted into this prestigious program marked the beginning of my journey in the United States.
During my college years, I sought every opportunity to gain practical experience by participating in externships with organisations such as FRA/Conrail, Never Fear Being Different, Ortho Clinical Diagnostics, and the Defense Advanced Research Project Agency (DARPA). These experiences allowed me to apply data science concepts to real-world problems, giving me a deeper understanding of the challenges associated with data cleansing and data gathering. While data scientists are often comfortable speaking in technical terms, these externships taught me the importance of translating technical metrics into actionable insights for business users. I realised that data visualisation is a crucial component in effectively conveying data insights.
While data scientists are often comfortable speaking in technical terms, these externships taught me the importance of translating technical metrics into actionable insights for business users.
Initially, I opted for the ECE concentration at Rutgers, given my background and comfort in the field. However, my curiosity soon led me to explore the burgeoning fields of big data analytics. As I delved into these areas through elective courses, I realised that this was where my true passion lay. The ability to derive insights from vast datasets and build predictive models fascinated me, and I decided to switch my concentration to analytics. This decision transformed my academic experience, as I found myself thoroughly enjoying every aspect of the program.
The combination of engineering and MBS training provided me with the best of both worlds. My engineering background strengthened my maths skills and problem-solving abilities, while the MBS program equipped me with a comprehensive understanding of both business and technical aspects. On the business side, I gained insights into finance, marketing, leadership, and communication, while on the technical side, I mastered data science techniques, statistics, AI, ML, regression analysis, Python, R, data structures, database creation, and SQL. This unique blend allowed me to apply data science techniques to make predictions and, more importantly, to convey those insights to business leaders in a language they understood. It helped me view problems from a business perspective and develop technical solutions to address them effectively.
Throughout my time at Rutgers, I developed a strong ability to learn and adapt to new technologies. The rapid pace at which technology evolves today demands constant learning, and I embraced this challenge wholeheartedly. Each semester brought with it the opportunity to master new software and programming languages, culminating in final projects that required me to apply these skills in real-world scenarios. This experience fostered a deep confidence in my ability to learn and master anything within a short time frame.
One of the key lessons I learned during my studies was the importance of basing solutions on the problems at hand, rather than the tools available. This realisation pushed me to step out of my comfort zone and explore various software and technologies, always striving to provide the best solutions for the challenges I encountered.
Today, as a data scientist at Integra LifeSciences, I apply these principles. I am passionate about creating and training models to achieve the desired outcomes, and I find great satisfaction in the process of exploration and innovation. The journey from ECE to data science has been one of continuous learning and adaptation, and I am excited to see where this path will lead me in the future.
I believe data science is like cream that can go on top of any cake. The analysis of data can be applied across various industries –whether it’s finance, healthcare, life sciences, the energy sector, nonprofit organisations, or technology –data science enhances and elevates the decision-making process. The versatility and impact of data science are what make this field so exhilarating.
Outside of work, I am committed to continuous learning and contributing to the data science community. As an ambassador for Women in Data Science (WiDS), an active speaker and a student mentor, I actively engage in initiatives to share my knowledge. In my free time, I read Kaggle Notebooks and GitHub to stay current with the latest data science techniques. Furthermore, I have had the honour of serving on the jury panel for the Globee Awards.
The world of AI and ML is ever-evolving, and I enjoy staying informed about the latest developments by reading blogs and connecting with others in the community. This exchange of ideas and knowledge constantly inspires and motivates me, reinforcing my commitment to contributing to this dynamic field. My journey has taught me that with curiosity, dedication, and a willingness to learn, it is always possible to turn ambition into achievement. As Albert Einstein once said: ‘The important thing is not to stop questioning. Curiosity has its own reason for existing’. I encourage everyone to stay curious and enjoy finding answers.
The analysis of data can be applied across various industries –whether it’s finance, healthcare, life sciences, the energy sector, non-profit organisations, or technology – data science enhances and elevates the decision-making process.
