Statistics and Data Science
The Master of Arts in Statistics and Data Science is designed to provide students with a comprehensive and interdisciplinary education in statistical methods, data modeling, and analytical technologies. Over the span of two years, the program develops a strong foundation in both theoretical statistics and applied data science. Students explore probability, regression analysis, multivariate methods, and statistical programming while also engaging with modern tools such as machine learning, big data platforms, and data visualization frameworks. The curriculum blends conceptual understanding with real-world applications, equipping graduates to extract insights from complex data systems and support evidence-based decision-making in various sectors.
Emphasis is placed on both rigorous academic training and hands-on practice, allowing students to refine their coding abilities in languages like R and Python, develop reproducible workflows, and tackle open-ended data problems. By engaging with case studies, collaborative projects, and optional internships, students build a versatile skill set that is relevant to roles in government, business, technology, healthcare, and academic research. Faculty mentorship, access to research centers, and a structured thesis project further prepare students for impactful careers or doctoral-level study.
Key information
Key Facts
- Program Title: Statistics and Data Science
- Degree Type: Master of Arts
- Duration: 2 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 01 February 2026
- Location: University of Pennsylvania, United States
- Field of Study: Statistics
- Language of Instruction: English
Program Structure
Semester 1 - Foundations of Statistical Analysis
• Probability Theory
• Statistical Inference I
• Statistical Computing with R and Python
• Data Ethics and Responsible Data Use
Semester 2 - Applied and Theoretical Methods
• Regression and Linear Models
• Statistical Inference II
• Exploratory Data Analysis and Visualization
• Elective (e.g., Causal Inference or Bayesian Methods)
Semester 3 - Advanced Applications and Specialization
• Machine Learning for Statistical Modeling
• Multivariate Data Analysis
• Time Series Analysis or Big Data Tools
• Elective (e.g., Computational Biology or Public Policy Statistics)
Semester 4 - Synthesis and Research
• Master’s Thesis
• Advanced Topics in Data Science
• Internship or Capstone Project
• Seminar in Statistical Practice
Career Opportunities
Graduates of this program are prepared to thrive in roles across industry, government, healthcare, academia, and nonprofit organizations where quantitative reasoning and data interpretation are crucial. Common job titles include data analyst, biostatistician, research scientist, machine learning engineer, policy analyst, and quantitative strategist. Many also go on to pursue PhD programs in statistics, data science, or applied fields. The ability to combine statistical rigor with programming proficiency and communication skills makes graduates valuable assets in sectors such as finance, pharmaceuticals, tech, education, and environmental science, where they contribute to optimizing operations, improving outcomes, and informing public policy with data-driven evidence.
Why Choose This Program
This program stands out for its integrated approach that unites mathematical foundations, computational techniques, and applied research experiences under one cohesive curriculum. Students benefit from a dynamic learning environment that emphasizes collaboration, innovation, and practical skill-building through real-world data challenges and customized project work. Courses are taught by faculty with active research portfolios and industry experience, offering students insight into both academic and professional applications of data science. With access to cutting-edge labs, internship opportunities, and strong post-graduate support, the program prepares learners to confidently address complex problems in data-intensive fields. For those aspiring to make a measurable impact through analytics, modeling, and thoughtful data interpretation, this program offers an ideal pathway to a fulfilling and future-oriented career.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 215 898 5000
Email: admissions@upenn.edu
Address: University of Pennsylvania, Philadelphia, PA 19104, United States
