Actuarial Science
The Master of Science in Actuarial Science is a one and a half year full time program designed for students seeking advanced expertise in risk assessment, financial modeling, and data driven decision making. The curriculum combines actuarial mathematics, statistical modeling, predictive analytics, and applied research to provide a comprehensive understanding of how quantitative analysis supports financial, insurance, and risk management decisions. Through this program, students develop risk modeling skills, statistical analysis expertise, predictive analytics competencies, and financial decision making abilities, preparing them to analyze complex datasets, forecast outcomes, and optimize strategies in corporate, insurance, and consulting environments.
This on campus program offers an interactive, application focused learning environment where lectures, workshops, and projects allow students to apply actuarial and data science techniques to real world financial and risk scenarios. Students refine financial modeling, insurance risk assessment, data visualization, and applied statistical research through collaborative projects and independent studies. Graduates are prepared to work in insurance companies, financial institutions, consulting firms, and risk management departments, equipping them to develop actuarial models, analyze large datasets, design predictive frameworks, and provide evidence based guidance for strategic decision making.
Key information
Key Facts
- Program Title: Actuarial Science
- Degree Type: Master of Science
- Duration: 1,5 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 01 June 2026
- Location: Columbia University, United States
- Field of Study: Data Science & Big Data
- Language of Instruction: English
Program Structure
Semester 1 – Foundations in Actuarial Science
• Probability and Statistics for Actuarial Applications
• Financial Mathematics
• Data Analysis and Predictive Modeling
• Research Methods in Actuarial Science
Semester 2 – Advanced Risk and Data Analytics
• Actuarial Risk Assessment
• Applied Statistical Modeling
• Seminar in Actuarial Data Analytics
• Applied Project in Risk Management
Semester 3 – Applied Research and Strategic Implementation
• Capstone Project in Actuarial Science
• Financial Risk Management
• Data Science Techniques for Actuarial Applications
• Elective Modules in Insurance, Finance, or Predictive Analytics
Career Opportunities
Graduates of this program are prepared for careers in insurance, finance, risk management, and consulting. Career paths include actuarial analyst, risk management consultant, financial modeler, data analyst in finance, and predictive analytics specialist. Graduates are equipped to evaluate financial risks, develop actuarial models, analyze large scale datasets, and support strategic decision making in diverse financial and corporate environments. The program also prepares learners for leadership and advisory roles in risk and actuarial teams, enabling them to implement data driven strategies, optimize risk management processes, and contribute meaningfully to organizational decision making.
Why Choose This Program
Students choose this program because it combines actuarial mathematics, data driven risk analysis, applied statistical modeling, and predictive analytics skills within a one and a half year intensive framework. The curriculum emphasizes both theoretical foundations and practical applications, allowing learners to acquire analytical, strategic, and problem solving skills necessary for success in actuarial science and risk management. Graduates gain the knowledge, confidence, and competencies to pursue careers in insurance, finance, consulting, and analytics while contributing meaningfully to evidence based decision making, risk optimization, and financial strategy in complex organizational settings.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 212 854 1754
Email: admissions@columbia.edu
Address: University of Columbia, Admissions Office, New York, NY, United States
