Graduates of Columbia University’s M.S. in Applied Analytics (APAN) program are applying data, machine learning (ML), and artificial intelligence (AI) to solve complex problems across industries. In a recent discussion with incoming students, two APAN alumni—Shivi Tandon (’25SPS), manager in marketing strategy and analytics at American Express, and Namira (Mia) Suniaprita (’24SPS), AI/ML platform engineer at the World Bank Group—reflected on how the program shaped their careers and expanded their professional possibilities.
From Exploration to Career Direction
The APAN program served as a pivotal turning point in Suniaprita’s career. She entered the program with an interest in pricing analytics and graduated into a more technical role focused on AI infrastructure and platform engineering. “This program was a transition phase for me,” Suniaprita said. “I came in with a specific end goal, but the Applied Analytics program encouraged me to follow my curiosity, and that ultimately reshaped my career direction.” Now, as an AI/ML platform engineer at the World Bank Group, she builds scalable, self-service AI platforms that enable data scientists, economists, and operational teams to deploy machine learning and large language models responsibly across the organization.
Building Confidence Through Applied Learning
For Tandon, the program was instrumental in strengthening her confidence in analytics and supporting her transition into the U.S. job market. “The program was a game changer for me,” Tandon said. “It significantly boosted my confidence in working with big data and analytics and completely changed how I approached data science.”
While enrolled, Tandon secured a summer internship with American Express, working on its investment optimization team. She now serves as a manager in marketing strategy and analytics at the company. “The skills we learn are highly marketable and can be applied on the job from day one,” she added. “I could feel the difference even one semester into the program when I started interviewing.”
Courses That Bridge Theory and Practice
Both alumni highlighted the program’s core curriculum, particularly Applied Machine Learning I & II, for its emphasis on real-world problem-solving. “Those courses completely changed how I think about AI,” Suniaprita said. “They showed us not just how models work, but how to implement them responsibly in real environments across multiple industries where the impact is tangible.” She later applied these skills during a consulting engagement with the United Nations, where she supported supply chain optimization initiatives for developing economies. In addition, the final Capstone project helped them develop experience in project scoping, stakeholder communication, and translating technical work into actionable insights.
“The Capstone project taught me how to scope real-world problems and build practical solutions,” she said. “You don’t just learn how to build a model. You learn how to productionize it and communicate its value across technical and nontechnical stakeholders.”
Learning Beyond the Classroom
Both alumni emphasized that meaningful learning extended beyond coursework. Participation in student organizations such as the Applied Analytics Club, along with hackathons, industry talks, and networking events, helped them build community and professional connections. “There’s a lot to leverage outside the classroom,” Suniaprita said. “I built connections that helped me grow just as much as my classes.” They also highlighted the role of the SPS Career Design Lab in helping students prepare for internships and full-time roles.
Above all, they encouraged students to enjoy the experience, stay open to evolving career goals, and take advantage of the many opportunities available both inside and outside the classroom. Tandon concluded with this advice: “The curriculum can be demanding, so stay focused on your long-term goals, make time to connect with others, and have fun.”
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.
