The M.S. in Applied Analytics (APAN) program is expanding its offerings with two recently announced concentrations. These concentrations will enable students to tailor their studies to the real-world industries and applications that interest them. Students will be able to choose between a concentration in Emerging Technologies and one in Quantitative Management Analytics.

To gain some industry perspective on how these concentrations will benefit students, we sat down with Cristian Leo, an alumnus of the APAN program who now works as a data scientist at Amazon. Leo began his career as a business and economics student in his home country of Italy. After taking a basic Python course, Leo was hooked on coding. Realizing his passion for data science late in his undergraduate studies, Leo pivoted his career path and enrolled in Columbia University’s master’s in Applied Analytics program. “Columbia’s Applied Analytics program not only provided me with comprehensive knowledge but also prepared me for a career in the field, ultimately leading to my current position as a data scientist at Amazon,” Leo said.

In this Q&A, Leo shares his perspective on his career journey and reflects on how the APAN program’s new Emerging Technologies concentration will prepare students for life after graduation. 

My degree from Columbia’s Applied Analytics program has been instrumental in my role at Amazon Cybersecurity, where our team serves as the AI/Science engine for the organization. The program didn’t just impart knowledge; it taught me a practical method for gathering and applying AI knowledge. One crucial skill I developed was the ability to read and understand data science research papers, which I now do daily. The mentorship and guidance from APAN’s professors were invaluable in developing this skill, which I couldn’t have acquired on my own. Moreover, the program’s comprehensive approach to data science has enabled me to tackle diverse challenges brought to us by internal customers, leveraging science and AI to solve complex problems in cybersecurity.

The new Emerging Technologies concentration is an excellent addition to the program, and I wish it had been available during my time as a student. In the rapidly evolving field of data science, especially in tech companies pushing the boundaries of innovation, studying current data science techniques is not enough. This concentration will benefit students by exposing them to cutting-edge technologies and methodologies that are shaping the future of the industry. It will help bridge the gap between academic learning and real-world applications, preparing students for the dynamic nature of the field.

Working at Amazon Web Services [AWS] in the AI cybersecurity space, I can attest to the relevance of these emerging technologies in my daily work. Cloud-based platforms are fundamental to our operations, as AI and data science at scale rely heavily on cloud infrastructure. Working with and understanding cloud technologies is crucial in modern data science roles.

Generative AI algorithms are at the core of my work, particularly in areas like Graph-RAG [Retrieval-Augmented Generation] and multi-agent systems. These advanced techniques are pushing the boundaries of what’s possible in AI and cybersecurity. 

The most disruptive element in data science is the rapid advancement of AI itself, particularly Agentic AI. These systems are achieving unprecedented levels of capability, sometimes appearing to match or exceed human expertise in certain domains. This can seem daunting for new learners, but it’s crucial to view AI as a powerful tool rather than a competitor.

To prepare for this future, students should focus on understanding the fundamentals of AI, develop skills in effectively directing AI systems, and cultivate critical thinking skills that compliment AI’s capabilities. The more that students can make AI work for them—not vice versa—the better.

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 at all levels within organizations.

The fall 2025 application deadline for the M.S. in Applied Analytics program is June 1. Learn more about the program here. The program is available full-time and part-time, online and on-campus.