Changing career paths is easier said than done, because there are no tried and tested approaches that work, its a risk one needs to take !

Swarna Gowri Thota, our next pathbreaker, Data Scientist at Pepsico (New York City), primarily tackles challenges related to understanding and optimizing consumer behavior based on data driven insights.

Swarna talks to Shyam Krishnamurthy from The Interview Portal about completing her PhD on Baker’s Yeast and transitioning to a career in Data Science by leveraging her background in statistics.

For students, develop a strong foundation in core technical skills which will definitely give you the needed edge and flexibility to pivot later in life !

Swarna, can you share your background with our young readers?

Last out of three girls, I was born and raised in a rural Simhachalam in Visakhapatnam into a lower middle-class household. Mom was a housewife (passed matriculation) while my dad worked as a minor clerk in state government (PUC+shorthand by education). My passion was music, and from childhood I excelled academically. “With studies I can earn some money and art doesn’t fill your stomach,” my parents often reminded me. I thus chose academics instead of that road; music was limited to listening and enjoyment. 

It was my mother who inspired me to pursue independence by means of education. Though I never knew what that career should be, my sole objectives were to study and land a job, till I was a bachelor’s degree graduate. Every choice I made from intermediate(12th) was appropriate at that time given lack of exposure and limited resources. 

What did you do for graduation/post graduation? 

After finishing my +2, I couldn’t clear the medical entrance exam. Although I considered trying again for another year, my enthusiasm for biotechnology led me down a different path. I was fascinated by recombinant DNA technology and genetic engineering. My passion for biotechnology drove me to complete both a bachelor’s and a master’s degree in the field. During my studies, I was exposed to various topics, but my experiments with baker’s yeast were a turning point. Yeast feeds on glucose and produces alcohol through fermentation. My curiosity about yeast biochemical pathways motivated me to pursue doctoral studies in yeast metabolism and biochemistry at CDFD (Center for DNA Fingerprinting and Diagnostics), Hyderabad. I took part in a nationwide entrance exam conducted by the Department of Biotechnology, Government of India, and achieved an All India Rank of 54. After passing a rigorous interview with CDFD, I secured my PhD candidature. I have always been passionate about becoming a biochemical scientist. 

Baker’s yeast is a tiny microorganism with numerous applications in biotechnology. However, the mechanisms governing yeast growth and culture are not fully understood. With significant assistance from my mentor, Dr. Rashna Bhandari, I was able to identify the biochemical pathways that control yeast growth.

My work involved extensive biochemistry and molecular biology. All biologists need statistics to present our data convincingly to the scientific community. From day one, I thoroughly enjoyed statistics and statistical methods. I never imagined that my keen interest in statistics would one day become my career foundation.

What were some of the key influences that led you to such an offbeat, unconventional, and unique career in Data Science after a career in Research?

By the end of a PhD program, everyone looks for options: pursue a postdoctoral fellowship and continue in academia, or explore alternatives such as science writing or grant management. In the third year of my PhD, I realized I didn’t want to be a scientist working at the bench doing experiments. Instead, I was interested in non-bench work, particularly data analysis and statistics, which I always enjoyed and excelled at. This early decision gave me clarity about my direction, though I was still unsure how to build a career away from the bench.

How did you plan the steps to get into the career you wanted? Or how did you make a transition to a new career? Tell us about your career path

Choosing an alternate career path is challenging, given the numerous options available. I spent several months exploring various possibilities. My husband suggested that if I wanted to switch careers, it would be best to choose one where my transferable skills could be maximized. This way, I wouldn’t have to start from scratch. It was the best advice I ever received. My strong background in statistics is a valuable transferable skill, so I decided to pursue data science without hesitation. 

However, this great decision came with a pause. I decided to take a career break when we became parents to our daughter. During this time, I also explored bioinformatics as a potential career option. Having an infant, I didn’t have much time to prepare for data science, so I worked as an NGS analyst intern at Albert Einstein College of Medicine. Meanwhile, I gathered resources, networked with people, and completed introductory courses in Python. 

I created my own curriculum tailored to becoming a data scientist, utilizing resources from Udemy and finished courses like statistics, SQL coding, Machine learning and python coding. 

After completing all the courses, I sought more hands-on experience through projects, as employers highly value project work during recruitment. I found that bootcamps are an excellent way to work on exciting projects and gain substantial experience in a short period. However, bootcamps can be expensive. Despite the financial struggle, I secured a loan and enrolled in a 12-week immersive bootcamp where I learned to design and execute data science projects. The bootcamp at Metis was an eye opener for me in terms of doing some real projects and meeting some amazing people who are experts at coding. The bootcamp was extremely intensive, requiring me to dedicate 14 hours a day to coding for 12 weeks. These programs recruit students who pass a written and online coding interview. I didn’t succeed on my first two attempts, but I got lucky on the third try. During the 12 weeks, we completed four types of projects: 1. Linear Regression, 2. Logistic Regression, 3. NLP, and 4. Deep Learning. This in-person bootcamp significantly boosted my confidence in executing real-life projects by sourcing data from the web, cleaning it, and applying machine learning techniques. All my projects are available on GitHub.

Even after the bootcamp, I continued working on my own data science side projects, building a portfolio and adding multiple projects to my GitHub repository. 

How did you get your first break? 

I was doing an internship at Albert Einstein, where my husband works. I wanted to expose myself to coding and worked with a bioinformatician learning coding in biological datasets. My husband helped my get the internship

After finishing the bootcamp at the end of 2019, and while waiting for my work permit, I pursued free internships and volunteering opportunities, continuing to network with people online. Although networking isn’t my strong suit, I did my best. The onset of COVID-19 and delays in getting my work permit further complicated my job search. During this time, I completed an internship analyzing the correlation between pollen data and asthma. When I finally received my permanent residency, my job applications began gaining traction. By the end of 2021, after several unsuccessful interviews, I landed a position as a data scientist at PepsiCo through a direct application. I was fortunate enough to make it all the way. 

What were some of the challenges you faced? How did you addressthem? 

Challenge 1: Choosing the right alternate career path has been crucial, and I initially struggled to figure it out. Many people I know who have changed their career paths also continue to struggle in their current roles. Selecting a new career path based on transferable skills is just a small piece of the puzzle. I believe everyone should fast forward to the future and ask themselves whether they will still enjoy their current role/work in 10 years. Does it offer a good work-life balance? While no one can predict the future with certainty, envisioning yourself 10 years ahead can help in making the right decision.

Challenge 2: Changing career paths becomes easier with a mentor. Unfortunately, I didn’t have one and had to figure out everything on my own, which delayed my career transition. I needed help at multiple stages: from coding, choosing projects, asking the right questions, polishing my resume, to interview preparation. Above all, I wanted a mentor to guide me to a company where I could fully utilize my expertise and enjoy my work. Whenever I get the chance, I try to help students who reach out to me on LinkedIn. 

Where do you work now? What problems do you solve?

I work at Pepsico as a data scientist. As a consumer analytics specialist, I primarily tackle challenges related to understanding and optimizing consumer behavior. I delve into consumer data to identify patterns and trends that influence their purchasing decisions. By profiling consumers, I determine their relevance to a brand and tailor marketing strategies accordingly. This involves a deep understanding of consumer demographics and brand orientation to ensure that products and services align with their preferences and needs.

What skills are needed for your role? How did you acquire the skills?

In addition to technical skills, a deep understanding of business principles and domain knowledge is a must. This knowledge enables me to align analytics efforts with business objectives and deliver actionable insights. I acquired these skills through a combination of formal education, hands-on experience, and continuous learning.

What’s a typical day like?

The day-to-day activities can be quite varied, but they consistently revolve around leveraging data to uncover meaningful trends and patterns. I may spend time cleaning and preparing data sets, exploring different analytical approaches, or communicating findings to stakeholders. The ability to effectively manage time and prioritize tasks is essential in such a fast-paced environment.

What is it you love about this job? 

What I find most rewarding about my job is the opportunity to solve complex data problems and make a tangible impact on businesses. I enjoy the challenge of unraveling consumer behavior and using data-driven insights to inform strategic decisions. The ability to build models that predict future trends and outcomes is both intellectually stimulating and professionally fulfilling. Additionally, I value the collaborative nature of my work and the chance to interact with talented individuals from diverse backgrounds.

How does your work benefit society? 

My work as a consumer analytics specialist benefits society in several ways. By understanding consumer behavior, I help businesses make more informed decisions about product development, marketing strategies, and customer service. This ultimately leads to better products and services that meet the needs of consumers and keep our customers happy. 

Tell us an example of a specific memorable work you did that is very close to you! 

One particularly memorable project involved analyzing consumer data to identify market segments where the data was readily not available. I have scoured through the data manually and uncovered hidden patterns in consumer preferences. That way, we were able to recommend the expansion of specific product categories and target marketing efforts to these segments. 

Your advice to students based on your experience?

My advice to students interested in a career in consumer analytics

1. To develop a strong foundation in technical skills,such as programming and statistics.

2. I encourage students to cultivate a curiosity about human behavior and a passion for data-driven problem-solving.

3. Building a solid understanding of business principles, and industry trends which is also essential for success in this field.

4. Finally, don’t be afraid to seek out opportunities for internships and hands-on experience to gain practical knowledge and build a professional network.

Future Plans? 

My future plans involve continuing to develop my expertise in consumer analytics. I am interested in delving deeper into advanced machine learning techniques, such as natural language processing and deep learning, to uncover even more valuable insights from consumer data. Additionally, I am keen on exploring opportunities to work on projects that have a positive social impact.