I’ve always loved trying new things and creating. I’ve been on six continents and am always planning my next adventure. My family and friends are usually keen to try my eclectic recipes. One of my hobbies is gardening: I’m trying my hand at growing exotic fruit trees and flowers. It’s relaxing and so far, so good.
From investment banking to McKinsey
In my professional life, I’ve also been entrepreneurial. I worked at a boutique investment bank prior to joining McKinsey. There, I led the quantitative strategy and analytics team, building it from a single person (me) to a large team. It was a fast-paced environment; I worked with incredibly talented individuals and I learned a ton.
In 2015, a recruiter from McKinsey approached me about an exciting data science role in one of McKinsey’s proprietary, client-facing solutions, Ingenuity, by McKinsey. It involved using cutting-edge technology and machine learning to deliver substantial client impact in the financial services and insurance industries.
The opportunity was too compelling to resist. What followed was a rigorous interview process that ensured I was the right fit for the firm, and the firm was the right fit for me.
I work with amazing people everyday
There were so many things about the firm I love. First and foremost: the people. You work with amazing people every day. Each one brings significant experience from in or outside of McKinsey. More importantly, even after our longest days, these are the people I wanted to have dinner with; we always shared some good laughs. The support my colleagues showed me, blew me away.
Lee, one of our solution managers and someone I worked with almost on a daily basis, taught me a lot about the importance and fine art of maintaining client relationships. He’s a genius at translating analytics into real client impact. Lee has given me really useful guidance on how to navigate some tough personal situations—acting as my mentor and my friend.
Richard, our former solution leader, always had an Excel trick ready for me and showed me, through his example, how to manage a growing team of data scientists and analytics translators. He never hesitated to get into the weeds with us to work through challenges. His successor, Doug, brought his extensive experience in operations to bear, taking our solution to new heights.
Gigabytes of data driving significant impact
The second thing that excited me about McKinsey was client impact. I worked on some fascinating problems that were intellectually stimulating and important to clients’ organizations. For example, one of my most memorable client projects was working with a credit insurance firm in the U.S.
Our team built a machine learning-based model with more than 2,000 different variables. It analyzed several gigabytes of data from more than 30 sources. This whole process took place in four months. The fast pace of the project was astounding. Such a process, in my experience, would have taken at least two years anywhere else.
This whole process, from model creation to the sales took place in four months. Currently, these new business partners are being on–boarded by the clients, who are anticipating significant impact as a result. The fast pace of the project was astounding. Such a process, in my experience, would have taken at least two years anywhere else.
Advice for data science recruits
Be confident, and be yourself.
Based in Silicon Valley, Ajai is a McKinsey data science alum, specializing in the insurance and financial-services industries; and is now a senior product manager with Amazon Web Services’ Artificial Intelligence (AI) team. Prior to McKinsey, he was a product manager at an investment bank in San Francisco. He has a bachelor's in applied mathematics and statistics from the University of California, Berkeley; and an MBA in marketing and operations from The Wharton School of the University of Pennsylvania.
For more information on McKinsey's data science career paths, visit mckinsey.com/TechCareers.