Thank you for honing my skills over this journey, says Divya Mehta, an alumnus of Great Learning’s PGP Data Science and Business Analytics Course. Read further to learn about her journey with Great Learning in her own words.
I am a working mother with over ten years of experience. I graduated with B.com(H) from the University of Delhi, pursued my master’s from Delhi School of Economics, and finally completed my Ph.D. in Finance in 2017. I was working alongside my Ph.D. My Ph.D. days were difficult since I was continuously jostling between career and studies, and it is also that during this time, I got married. So, family, career, studies were all going alongside, and I was sometimes prioritizing one over the other. After finishing my Ph.D. in 2017, I was on my family’s way, and hence different sets of responsibilities were coming my way. Now the struggle was different. I had a baby in 2018, and I had no maternity leave. I took a one-month break and got back to work. Life was challenging with such a small baby, and this also posed challenges with my commitment to work.
A year later, I started feeling dilapidated and wanted to prove myself back at work. I felt that maybe upskilling would help. Since my Ph.D. has made me realize my love for analyzing data. Finance is a numbers field, and that blends nicely with the data science space. Hence, I decided on doing a course on data science. after a lot of research, I found DSBA from GL to be a nice course that will help me acquire new skills and widen my current knowledge. I am still pursuing this course and wish when I finish this course, I will be able to capitalize on the opportunities.
Well, we see quite a smaller number of women in data science when we define analytics professions. However, we significantly underestimate the number of women who are actually involved in data analytics. I think all women are involved in analytics even if they are a professional or a homemaker. Therefore, why not pursue a profession in data science. Data scientists are expected to solve complex real-world problems based on data trends and patterns, and thus, a combination of soft skills and specific profile or job-related skills is required. The same must be encouraged in women.
Women who want to pursue data science as their career must understand the fact that it requires absolutely no prior knowledge of coding. Hence, a transition to this will not be difficult at all as long as one is ready to put in the hard work. My simple advice would be if one is uncertain about their interests and are still on an exploration spree, begin with short-term data science training. This will help in understanding the course. This field is not linked to one particular field. The application of data science is in almost every field one can think of. After thorough research, I chose GL after reading and understanding their curriculum, hands-on learning experience, a well-curated course helping understand the application of data science into various fields. I was clear on the front that such a course is required to upskill. Again, career, studies, family all were back in action with me. But somehow, I managed between all three since the work from home option was there due to covid.
I am still pursuing the course. However, soon after the course, I intend to apply for the jobs available on the job portal made available by GL. This course, however, has definitely boosted my confidence since the skill is upcoming and well required in the job market. This has made me optimistic, and I feel secure about my future. I thank Great Learning for having great faculty and honing my skills over this journey. Priority to all of them, late nights became norms for me since the day would go for office work and family, but the sacrifice and toil are worth it. Even weekend plans would also need to be modified, and my family greatly supported me every time, including my seven years old sons.
The newly acquired skill has helped me to think of ways to implement machine learning in my own professional work and utilize the numerous amounts of data generated by Payroll products. I have got several ideas to implement and, in a way, improve the product and make it more market competitive.
