– I’m Taras, a senior manager in analytics, based out of McKinsey’s North American Knowledge Center in Waltham, MA. I the proud father of an 18-month-old daughter and I love spending time outside, hiking, kayaking and fishing.
I came to the firm almost nine years ago after finishing my doctorate in materials science engineering at MIT. I always wanted to be a scientist, but towards the end of my PhD, I started to feel a little isolated. I was researching a very niche topic only few people in the world knew anything about. I wanted to explore options outside of academia and consulting seemed like a great field. When I started engaging with McKinsey, I was very impressed by the quality of the people at the firm, how smoothly the recruiting process ran, and how precise and organized everything was. I wanted to learn how to do things this way to become a better leader.
When I joined the Stamford office as a generalist, I did not plan to stay very long. I’d even made a deal with my PhD advisor to come back to research if McKinsey didn’t work. I had good time my first couple of years. I learned a lot about how businesses run and I improved my communication and leadership skills.
At the same time, I never felt like the generalist role was quite right for me long-term. For me, the downside of being a generalist was that I felt like there wasn’t enough continuity from one engagement to the next. I wasn’t building expertise in an area of content and I missed that. I get excited solving difficult problems.
I started exploring other options and found analytics. At that time, the New York office was looking to build out its analytics team. One of the partners leading that effort was one of my mentors. He invited me to join. This was before the big data era; no one in the business community was really talking about analytics yet. Yet, I loved the idea of going back to math, building my own team, and becoming a manager, so I seized the opportunity. It was great fit. I was so happy to spend most of my time on content – writing code and building models. I could develop a vision for the team and implement it, while still working on many cool projects to which McKinsey alone can provide access. I found a community and great sense of belonging. I learned what so many of my colleagues had meant when they encouraged me to “make my own McKinsey.”
Since then, our team has grown from three people to more than 100 data scientists. We work on topics including artificial intelligence, neuro-linguistic programming and the internet of things and apply those to problems ranging from preventing terrorist attacks to improving college graduation rates. I feel very fortunate to have had the chance to build something meaningful in my career.
I’ve also mentored many of our newly hired colleagues to help them transition from students to successful professionals. In a way, McKinsey has enabled me to do what I always wanted to do in academia – solve new problems and teach – in a much more dynamic and exiting way on real world problems.