Tech opens doors and builds new pathways. That’s the lesson Shivani Singh, a recent graduate of the M.S. in Applied Analytics (APAN) program, took away from her time at Columbia and carries with her as she continues her professional journey.
With a background in data science and business strategy, Singh came to Columbia with an MBA and a mission to make technology more accessible. She previously worked at major companies such as Virtusa and Prudential Financial, where she led efforts to improve the customer experience through optimization technology projects. She is now a data scientist at Amazon and credits the lessons she learned at Columbia with preparing her to pursue this career.
Can you tell us about your journey to this field and to Columbia?
My interest in this field started with a simple curiosity: how can we use technology to make life easier for people? I started thinking about this question while working on a project to help develop a new computer chip in India. After gaining experience in business and consulting, I realized that the real magic happens when you combine data with a clear business strategy. At Virtusa, I spent several years leading data science consulting projects to implement customer feedback and develop solutions.
I soon realized that the most significant challenges weren’t just in building models, but at the intersection of applied analytics and business strategy. I wanted to move beyond “doing” data science to “defining” data strategy in the heart of the global tech industry. To me, Columbia’s APAN program curriculum perfectly bridges this gap.
What was your favorite experience from the APAN program?
The collaborative intensity of the capstone project was by far my favorite experience at Columbia. It was the culmination of everything we learned—taking a complex, real-world dataset and transforming it into a strategic narrative for stakeholders. Beyond the classroom, my favorite memories are the late-night brainstorming sessions with my cohort, working on everything from homework to group projects. Being surrounded by such a diverse, global group of peers expanded my perspective on how data is leveraged across different industries and cultures, which has been invaluable in my international work.
Did you have a particularly challenging or surprising experience in the program? What did you learn from it?
The most valuable challenge I faced was learning how to translate “data speak” into plain English. During my internship at Prudential Financial, I was building an AI-powered voice assistant to help customers with their insurance questions. I was very focused on the complex coding behind it, but I quickly realized that my managers cared most about one thing: the time and frustration we were saving customers. A brilliant model is only useful if you can explain its value to the people using it. It’s a lesson I carry with me every day in my current role at Amazon.
How might the new APAN program concentrations (Emerging Tech & Quantitative Management) benefit students?
As someone working in the tech industry, I see these concentrations as highly relevant to our field’s ever-expanding scope.
The Emerging Technologies concentration provides a more structured framework for the electives within the existing curriculum, giving students an intentional pathway to engage with rapidly evolving technologies. Technology is moving incredibly fast, especially with developments like AI assistants. With a curriculum designed to incorporate new tools and innovations as they emerge, students will have a dedicated space to explore the technologies shaping the future and get ahead of the curve.
The Quantitative Management concentration offers another tool to better equip students preparing to enter the workforce. In complex environments like digital advertising or finance (where I interned at Prudential), algorithmic decision-making is the backbone of the business. Students who can navigate optimization modeling will be prepared to lead teams that don’t just report on data, but actually automate high-stakes business logic.
What advice would you give to incoming APAN students?
Be a “builder” from day one. Don’t just complete the assignments; look for ways to apply what you’re learning to real-world problems. Use the Columbia network to its fullest—NYC is an incredible place to grow your network.
Most importantly, lean into the “Applied” part of the APAN title. Always focus on the “So what?” of your analysis. Especially when you are using a very complicated technical architecture, always ask yourself how your work changes a business outcome. That mindset—focusing on the human impact of your work—is what will truly make you stand out.
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.
