From Innovation to Impact: Navigating the Landscape of Data Science with Goda Ramkumar

In our latest podcast episode on Leading with Data, we were honored to host Goda Ramkumar, Vice President of Data Science at Swiggy. With over 17 years of experience, Goda has spearheaded the development of machine learning and optimization-based decision support systems across diverse sectors, from hyperlocal delivery to airline pricing and revenue management.

Her expertise in setting up successful data science teams and driving sustainable business impact is unparalleled. With a passion for teaching and a track record of impactful publications and presentations, she brings a wealth of knowledge in operations research, machine learning, and data analysis to the table. Tune in as she shares invaluable insights from her journey.

You can listen to this episode of Leading with Data on popular platforms like Spotify, Google Podcasts, and Apple. Pick your favorite to enjoy the insightful content!

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Key Insights from our Conversation with Goda Ramkumar

• The transition from traditional methods to data science is gradual and requires adaptability to new tools and technologies.
• In the airline industry, data science applications have a long lead time, contrasting with the real-time decision-making required in ride-sharing services like Ola.
• Building a strong tech brand is essential for attracting top talent in data science.
• Hands-on problem-solving and a strong understanding of business problems are crucial skills for data scientists.
• Generative AI is a powerful tool that can enhance productivity and creativity, but it should be used responsibly and not seen as a replacement for human jobs.
• The ability to adapt and upskill quickly is vital in the ever-evolving field of data science.
• A strong peer network and exposure to a variety of problems can accelerate learning and adaptability in data science careers.
• Fundamental skills in math, coding, and first principles thinking remain essential, even as new tools like generative AI emerge.

Join our upcoming Leading with Data sessions for insightful discussions with AI and Data Science leaders!

Now, let’s look at the details of our conversation with Goda Ramkumar!

How did you Transition from Biotechnology to Data Science?

When I was studying at IIT Madras, I was majoring in biotechnology, which was quite a happening field at the time. However, I realized that working in a lab with microorganisms wasn’t my forte. I was more drawn to operations research, which was my minor. It wasn’t called data science back then; it was all about math, stats, optimization, and what we now refer to as traditional methods. My first job was with Sabre, which was the only company hiring in the operations research field on campus. Over time, my role evolved, and without realizing it, I was transitioning into data science. It’s been a rewarding journey, and I’ve stayed in data science across multiple companies ever since.

What was it like Working in the Airline Industry with Sabre?

Sabre was focused on the airline domain, which has been applying tech since the seventies. I worked mainly in pricing and revenue management, dealing with forecasting, optimization, and inventory control algorithms. The airline industry has a long lead time to solve problems, unlike the real-time challenges I faced later in my career. Over my ten years at Sabre, the tools we used evolved from SaaS to R to Python, and we had to adapt to the changing talent market and technological advancements.

How did your Role Evolve at Sabre?

Every few years, I would contemplate a change, but my role would evolve in a way that kept things interesting. I moved from client handling to building next-generation algorithms, then into a people management role, and finally, I led the rewrite of the revenue management product. Each transition brought new challenges and learning opportunities.

What was the Transition to Ola like?

Moving to Ola was like crash-landing from air transportation to ground transportation. The pace was incredibly fast, with decisions needing to be made in milliseconds instead of days. It was a culture of rapid experimentation and learning, and I gained a wealth of experience in those two years. The problems we tackled at Ola felt unique, and we often had to come up with innovative solutions without much prior reference.

How did you Approach Hiring Talent at Ola?

Building a strong tech brand is crucial for attracting top talent. If you have a good pool of candidates, you can truly select the best. I look for coachable skills, strong fundamentals in coding and first principles thinking, and a positive attitude. Hands-on assignments and case studies help in evaluating candidates more effectively than just interviews. And of course, there’s always a gut feeling that plays a role in the final decision.

What Drew you to xto10x and then Swiggy?

At xto10x, I had the opportunity to work with a variety of startups across different domains, which was incredibly enriching. However, I missed being closer to the problem-solving aspect, which is what drives me. Swiggy presented amazing problems to solve, and it was a natural transition for me, especially during the COVID-19 pandemic when Swiggy’s role became even more critical.

How do you see the Role of Generative AI in Data Science?

I view generative AI as a tool, not a replacement for people. It can increase productivity and creativity if used responsibly. The roles and jobs will change, but there will always be enough to do. The key is to adapt and upskill at the pace of these changes. I believe in the resilience of human society to adapt and find new ways to utilize our time and skills.

Summing-up

Goda Ramkumar’s journey from biotechnology to data science is a testament to the power of adaptability and continuous learning in navigating the evolving landscape of technology. Her extensive experience and expertise in building data science teams and driving impactful solutions across diverse industries highlight the immense potential of this field. As we reflect on her insights into the role of generative AI and the importance of fundamental skills, we are reminded of the ever-increasing significance of responsible innovation and human adaptability in the realm of data science.

For more engaging sessions on AI, data science, and GenAI, stay tuned with us on Leading with Data.

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• Source: https://www.analyticsvidhya.com/blog/2024/04/navigating-the-landscape-of-data-science-with-goda-ramkumar/