A different path
I was born in Iran and moved to the United States in my early twenties. If I had gone into the family business, I would be an orthodontist like my brother and sister, but I took a different path and went deep into AI.
I taught myself to program in high school and kept building on that curiosity. In college, I took formal coursework in statistics, combined with a wide range of online courses. That gave me both the theoretical foundation and hands-on experience I needed to get serious about machine learning.
After finishing my PhD, I joined QuantumBlack, McKinsey’s AI arm. I started out working on optimization and forecasting models, and that work helped lay the foundation for Frontline AI, McKinsey's AI-powered workforce management platform. It helps clients optimize their operations through advanced forecasting and scheduling; it can also create AI agents that assist employees or function autonomously. I’ve filed several patents along the way and stayed close to the technical side throughout.
Most of my work today focuses on transforming operations, or what we call “rewiring” organizations, by using AI. That includes building voice and chat agents to automate customer calls, copilots that guide call center reps in real time by summarizing interactions and suggesting next steps, and back-office tools that automatically generate appeal letters or process complex workflows.
A technologist, a humanist
The common thread is applying AI in a way that improves how people work, for example, reducing repetitive tasks, accelerating onboarding, and making it easier for teams to focus on what really matters. The work is technical, but it is also about behavior change and adoption. I often work closely with operations teams, engineers, and business owners to make sure the solutions are not just accurate, but also trusted and embedded into how people work, such as by integrating with their daily tools or designing around real edge cases from the field. We’ve seen big breakthroughs happen when we slow down at the start to codesign with frontline users. That up-front investment always pays off in adoption and impact.
“We were close to pulling the plug.”
One high-stakes project that stands out was when we were deploying a real-time AI agent in a production environment, and the first version started to crack under unpredictable edge cases. It wasn’t a model issue but rather how the system handled interruptions and fallback logic. We were close to pulling the plug. What saved it was the resilience of the team. Instead of trying to patch over the problem, we rebuilt the system around failure by setting up better monitoring, more robust guardrails, and smarter recovery paths. The tech got better, but more importantly, the process reminded us that reliability is not just a feature, it’s a mindset.
QuantumBlack, AI by McKinsey
“Psychological safety comes first.”
As a leader of the data science guild at McKinsey, I also help define our technical vision, mentor others, and make sure what we build is scalable, safe, and grounded in impact for clients. I look for ambitious but generous people who hold themselves to a high standard and also take the time to coach others and help the team grow.
To foster strong teamwork, psychological safety comes first. People need to feel like they can ask questions, share concerns, and challenge ideas.
I remember a moment when someone asked a very direct question about whether we were solving the right problem. It was uncomfortable at first, but it opened up one of the best discussions we had on the project. That moment reminded me how valuable it is to create space for open, honest input. Good teams make time for those questions, and great teams act on them.
The teams are a big part of what I love about McKinsey. There is a mix of ambition and flexibility here that I really value. People aim high, but they are also open to rethinking their approach when something is not working. That mindset is rare and powerful. It is also the people. You are constantly surrounded by others who are pushing the boundaries of what is possible, and that energy is contagious.
My advice to young technologists? Stay close to real problems. Tools will come and go, but if you understand the context and the user, your solutions will have enduring impact. In a field that moves fast, anchoring your work in real human needs is what keeps it meaningful...and enduring.