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Applied Mathematics - Data Analytics

Making sense of the large amounts of data that are being produced in business, industry and government requires a combination of mathematical modeling, programming and analysis. Data analysts combine these tools to solve complex problems and make informed decisions.

Why Choose Applied Mathematics - Data Analytics?

In our graduate program you will master probabilistic modeling, data mining and machine learning, operations research and statistics, and work on projects that combine these tools to solve complex problems and make informed decisions.

Analytics is one of the fastest growing fields in business, industry and government. According to the Bureau of Labor and Statistics, job growth in this field will increase by 30% in the next 10 years.

Programs Offered

We offer three different program options, 5-year B.S./M.S., M.S., and Certificate, to accommodate students of virtually all levels.


If you have a quantitative undergraduate degree and have taken Calculus I-II-III, Linear Algebra and Probability, then our 30-credit M.S. in applied mathematics - data analytics program provides students with experience in:

  • computational methods
  • applied linear algebra
  • statistical methodology and probabilistic modeling
  • machine learning
  • operations research and non-linear optimization
  • database methods

You will use computing and programming environments such as MATLAB, R and Python. You can also take electives in mathematics, business and computer science. 

As part of the M.S. program, students are encouraged to complete internships. Recent students have interned for UPS, Blackrock, 1010 Data and the New York State Research and Development Authority (NYSERDA).

5-Year B.S./M.S.

Our B.S. in Mathematics/M.S. in Applied Mathematics - Data Analytics students work with the graduate director to design a program that allows them to begin with graduate study in their junior year, and to finish the combined program in 5 years. As an undergraduate student, you will begin with calculus classes, which are enhanced by computational software such as MAPLE. Undergraduate courses in linear algebra are enhanced using MATLAB and statistics courses use R. Courses in abstract algebra and analysis build depth. You can do an independent study or choose from a wide range of elective topics, including:

  • statistical inference
  • applied statistics
  • mathematical modeling
  • operations research
  • machine learning

We also offer a 18-credit post-baccalaureate certificate for students who have a bachelor's degree in a quantitative discipline and a strong background in mathematics.

The Community

Small classes foster collaborative problem solving and knowledge sharing. You will become a part of a caring and creative campus community, developing strong relationships, both with peers and professors. 

If you want to pursue research in a particular topic, our faculty members are eager to collaborate with you, and mentor you to present your work at professional conferences.

The Experience

Our New York City location is just minutes from the nation’s top financial and tech industry companies. Intern with established companies, like UPS or Google, or get in on the ground floor in New York’s booming tech startup industry.

  • Meet an Applied Mathematics - Data Analytics Graduate Student: Katherine Encarnacion
    Meet an Applied Mathematics - Data Analytics Graduate Student

    "I earned my bachelor’s degree in Mathematics from Manhattan. I'm the first generation in my family to go to college and I felt very insecure about my ability to understand all of the course material. My professors noticed that I lacked confidence, and definitely helped me overcome that. They were so helpful during my four years of undergrad that I felt like I could take on the challenge of graduate school.

    "I originally chose Manhattan College for its location and size. I grew up in a small town in Pennsylvania — I wanted a big city experience without being too bombarded by crowd. I had visited a couple colleges in New York City, and I felt like those campuses were too spread out. When I visited Manhattan it felt like a really welcoming, tight-knit community. Having a more traditional campus made a big difference.

    "In my MATH 492: Mathematical Modeling course we partnered with Assistant Provost David Mahan, formerly executive director of institutional research and assessment. We used statistical analysis to define patterns in and identify factors affecting student retention, engagement at Manhattan. It was my first experience applying complex math to solve a real world problem.

    "One of the biggest takeaways from the Master’s program so far, is that if I don't know something, I know I have the problem-solving and research skills to figure it out.

    "It was very messy - there was a lot of stuff missing and just trying to figure out exactly how to get results. The experience showed me that nothing will ever go exactly as planned. It was a glimpse of what it's like to have a career in mathematical modeling, and to work with at team. Nothing that is truly fulfilling comes easy. The fact that we worked so hard to get there, once it was done I felt an huge sense of accomplishment.

    "The summer after I graduated, I interned with CPXi, a digital media holding company in midtown Manhattan. I found the opportunity through the Office of Career Pathways' Jasperlink job board and recruiting platform. As a publisher operations support intern, I assessed daily digital media reports from several different websites and help value the space for potential buyers in real-time bidding. It was really exciting. The experience helped me honed my computer skills.

    "I used so many of the skills I learned in my modeling course, especially Microsoft Excel. So I was very happy that I had that experience from my course that gave me the extra push to get the internship.

    "The graduate experience is very different. The class size is smaller than undergraduate  like a cohort, we help each other out. There are more projects and the pace is faster. Generally, more is expected of you. I’m also starting to feel a little more pressure in finding a job after graduation. I’m excited to start the job search.”

What Will You Learn?

You will learn methods in computing, statistics and machine learning with a deep understanding of the mathematics in these methods. As a data analytics student you will:

  • Develop programming skills to solve problems in predictive analytics and applied mathematics
  • Gain confidence using analytics and data visualization software
  • Learn how to use probability models including random variables, Markov chains and queuing theory

See degree requirements

What Will You Do?

With an advanced mathematics degree, you will be prepared to work in data science, actuarial science, operations research, statistics, software engineering, and finance. Recent graduates have found employment opportunities with UPS, Blackrock, Accenture, Celonis and 1010 Data. The master's program will also prepare students who wish to pursue Ph.D. programs in statistics or data science.