After working across analytics, consulting, and business roles, Zaigham Khan began to notice a common challenge: organizations increasingly needed professionals who could do more than analyze data. They needed leaders who could translate insights into action, communicate effectively with stakeholders, and help drive strategic decisions.
By the time he arrived at Columbia University, Khan already held a bachelor’s degree in computer science, an MBA, and six years of professional experience. Looking to build on that foundation while deepening both his technical expertise and leadership skills, he enrolled in the M.S. in Applied Analytics program.
Today, Khan is an associate director of data science at Merck, where he works at the intersection of analytics, business strategy, and healthcare. In a recent interview with SPS, he reflected on his experience in the Applied Analytics program, discussed the rapid evolution of AI, and shared advice for new students.
Tell us about your current role at Merck.
As an associate director of data science at Merck, I lead analytics work in precision medicine and new products. My role sits at the intersection of data science, business strategy, and healthcare impact.
This is a particularly exciting time to work in analytics because AI is creating new opportunities to solve problems differently, faster, and more effectively. I partner with business teams to understand their challenges and use data science to help answer complex questions.
My favorite part of the job is knowing that our work is not just theoretical. It has the potential to support better business decisions and, ultimately, help improve how healthcare solutions reach patients. Being part of this AI-driven era while working on problems that can have a real-world impact on patients is incredibly motivating.
You’ve worked in the pharmaceutical, media, and consulting industries. How similar or different is data science and analytics work across those sectors?
Across industries, the core principles of data science and analytics are very similar. Every organization is trying to make better decisions, improve efficiency, understand customers or stakeholders, and optimize outcomes.
What differs is the maturity of data adoption and the business context. Some industries are further ahead in using data and advanced analytics, so the challenge is to continue innovating and finding new sources of value. Other industries or teams may be earlier in their data journey, where the challenge is often to build trust, educate stakeholders, and encourage evidence-based decision-making.
Consulting brings another dimension because you have to quickly understand a client’s business, demonstrate value, and communicate impact clearly. In industry roles, you often go deeper into the business over time and focus on creating sustainable, long-term value. Both experiences are valuable, and both have shaped how I approach analytics today.
How have you applied what you learned in the Applied Analytics program to your career?
The Applied Analytics program prepared me for this role in several important ways. The curriculum provided a strong foundation in statistics, analytics, and emerging technologies while also emphasizing business application and leadership.
One of the most valuable aspects of the program was its use of case studies and collaborative projects. These experiences helped me think through real-world business problems, structure analytical approaches, and communicate recommendations clearly. The program also placed a strong emphasis on storytelling and presenting findings to different audiences, which is something I use almost every day in my current role.
In my work, I frequently present insights to both technical and nontechnical stakeholders. The ability to translate complex analysis into a clear business narrative is critical, and the Applied Analytics program helped me build that skill. The networking opportunities were also valuable. They helped me better understand the market, learn from peers and industry professionals, and prepare for the skills needed to succeed in analytics leadership roles.
What was your favorite experience or memory from the program?
My favorite experience was interacting with classmates and professors before, during, and after class. The diversity of the Applied Analytics community was one of its greatest strengths. Students came from different countries, industries, and professional backgrounds, and everyone brought a unique perspective.
Those conversations often extended beyond coursework and helped me see problems through different lenses. Learning from people with such varied experiences was extremely valuable and remains one of my most memorable parts of the program.
Is there a specific issue or topic (for example, AI) in the field of analytics that you think is particularly relevant to the future of the industry? How can current students prepare for it?
There is no way to shy away from AI in this day and age. It is becoming part of almost every industry, and students should take every opportunity to learn about AI, experiment with new tools, and understand how these technologies are being applied in the real world.
At the same time, students should not lose sight of the fundamentals. The tools will continue to evolve, but the foundations of statistics, data quality, experimental design, critical thinking, and problem framing remain extremely important. AI can be powerful, but it still requires people who can ask the right questions, evaluate outputs, understand limitations, and connect results to business decisions.
Storytelling is also key. The ability to explain complex ideas simply and persuasively will continue to differentiate strong analytics professionals. I would also encourage students to network with industry professionals early, understand where the market is going, and continuously build skills that align with real business needs.
What advice would you give to new students?
The Applied Analytics program can be a career-changing experience, so my advice is to make the most of it. Enjoy the journey, but also be intentional about preparing yourself for the industry.
Network actively, build lasting friendships, and learn from your classmates and professors. Take time to understand the job market and the skills that employers value. Most importantly, do not treat projects as assignments completed solely for a grade. Take them further. Build something you are proud of and can speak about in interviews, seminars, and professional conversations.
The program gives you a strong platform, but what you do with that platform is what will shape your career.
About the Program
Columbia University’s Master of Science in Applied Analytics prepares students with the practical data and leadership skills to succeed. The program combines in-depth knowledge of data analytics with the leadership, management, and communication principles and tactics necessary to impact decision-making across industries and organizational functions.
Learn more about the program here. The program is available full-time and part-time, online and on-campus.
