Career stories: Next plays, jungle gyms, and Python
June 29, 2022
Since she was a child, Deepti has been motivated to help people. This drive led her on a career journey with many pivots and moves — akin to navigating a children’s jungle gym — between industries and around the world. Based in Bangalore, this biomedical engineer turned data scientist shares how LinkedIn helped her gain new technical skills, dive into meaningful work, and grow.
Growing up in Mumbai, India, I always imagined myself in a career where I could give back. I once dreamed of becoming a neurosurgeon, but early in my career, I took a different path and earned a bachelor’s in electronics engineering. While studying engineering gave me the foundation for my future career, I quickly realized that my job options wouldn’t help me make the difference that I wanted to. So, I decided to complete a master’s program in biomedical engineering at Drexel University in Philadelphia.
After graduating, I found an opportunity at the Toyota Technical Center in Boston, where I helped build driver safety systems that incorporated human physiological considerations into injury prevention. Toyota is where I first began to reconsider my perspective on what it means to help others, realizing that I could draw on my STEM background to build safer systems that would benefit everyone.
Embracing a data-driven career change
Soon, however, home and family called me back to India where at the time, biomedical research in India was not as exciting as the work I was doing in the U.S. While CT scans and MRIs are, of course, critical instruments, I increasingly felt that I wasn’t giving back in the way I’d hoped. After two years, I knew it was time to push myself out of my comfort zone once again, which led me to data science.
When I first broke into the field, data science was more like informal analytics. Yet I was intrigued by this new discipline, where I could use the skills I gained as an engineer, like problem-solving and logical thinking, while also gaining unique expertise. When I started, my mantra was to keep focused on learning and not worry about my experience (or lack of) when surrounded by data scientists, who were just out of school, with more experience than me.
My instincts served me well, and I quickly grew from an analyst to a senior manager — this pace of career progression is the norm in startups, where fast growth is expected. In a short period, my time became less focused on getting my hands dirty with data, and more centered on managing clients and stakeholders and putting out fires. After seven years, I missed building things and solving problems, which is when the perfect opportunity opened up at LinkedIn.
Giving back to the global community at LinkedIn
With a desire to do more, I was recruited at the right time for a data scientist position on LinkedIn’s Economic Graph, our digital representation of the global economy. The Economic Graph research team I was on was a global team with people based in the U.S., Europe, and Singapore. What appealed to me most about the Economic Graph was that we work and collaborate alongside the government and other non-governmental organizations (NGOs) to deliver insights that enable our members to succeed and connect with the right opportunities for them.
The Economic Graph partners with public sector organizations to provide data insights that improve policy decisions. For example, if a government ministry is considering where to invest in education, they need data on issues like labor market demand and skills gaps. Using our member (i.e., LinkedIn user) data, our team would deliver such power-packed insights using LinkedIn platform data. At LinkedIn, we ensure that member data is used safely, and we’re proud that the trust we’ve built with our members enables us to deliver these insights.
Python, Scala, and people management
When the Economic Graph team consolidated, I knew it was time for the next stage of my career, or my Next Play as we call it here. My manager pushed me to consider taking on a tech lead role in data science within the Business Operations team at LinkedIn in India. I admit I was reluctant to go back to a position focused on business revenues, as I had grown attached to the research mission in my previous role. Soon, though, I realized that everything we do at LinkedIn helps advance our mission and vision for the community.
Now, I’m managing a newsletter and leading a team of data scientists solving business-critical problems across the company. It’s precisely the kind of exposure I’m looking for at this point in my career, gaining horizontal expertise by engaging all these different domains. LinkedIn is all about learning. Here, managers encourage people to take charge of their careers, experiment, and move into other roles according to their interests and goals.
We don’t shy away from challenges and learning curves. For example, I’ve had to upskill myself in coding. For nearly 14 years, I primarily used the R programming language. Now, we’ve moved on to Python and Scala, building on our everyday work with statistics and math.
It’s not all about tech, though. We deal with unique questions, so problem-solving skills are critical. It’s also essential to think about the business contexts and ask the right questions. Then, we bring it all together with technology to solve a problem in a structured manner.
Moving forward on the LinkedIn learning path
When thinking about career trajectories, I always return to this metaphor of a children’s jungle gym. I tell my team that it’s about moving through a matrix rather than climbing a ladder one step at a time. You’re still moving from one point to the next, but the next step isn’t necessarily upward. The reality is that, sometimes, you have to move down a level to reach a specific endpoint.
I’ve moved from senior management roles into positions with no one reporting to me. At first, I thought, “Am I down-leveling?” Then I would remind myself that my final goal is always to do something meaningful. At that point, taking on a more technical role was a step in that direction.
Then, with the knowledge and expertise I gained, I could return to leading teams and tackling more considerable challenges. Growth looks different to different people but as long as you have that fire inside you to keep learning and growing, changing domains, jobs, or even countries, it will only help you in your journey.
Based in Bengaluru, India, Deepti is a senior data scientist at LinkedIn. Before LinkedIn, she spent nearly seven years as a senior analyst and senior manager for 7.ai working on customer engagement solutions. Born and raised in India, she holds a bachelor’s degree in electronics engineering from the University of Mumbai, and a master’s in biomedical engineering from Drexel University in the U.S. Outside of work, Deepti spends time with her two daughters, and shares her passions for interior design and gender equality issues on social media.
Editor’s note: Considering an engineering/tech career at LinkedIn? In this Career Stories series, you’ll hear first-hand from our engineers and technologists about real life at LinkedIn — including our meaningful work, collaborative culture, and transformational growth. For more on tech careers at LinkedIn, visit: lnkd.in/EngCareers.