pause world-wide-web instagram volume-medium linkedin flickr basketball devices home pencil person-money rss slider-left-arrow slider-right-arrow slider-left-arrow slider-right-arrow star video-transcript close hamburger minus plus account arrow certificate city globe graduation-cap graph handshake info info-2 map play search snapchat twitter facebook file-text-o youtube tumblr camera file-text

Applied Mathematics - Data Analytics - M.S

Making sense of the large amounts of data that are being produced across industries requires the work of data analysts, who can solve complex problems and make informed decisions.

Why Choose Applied Mathematics - Data Analytics?

This badge signifies our applied mathematics - data analytics program is a stem-designated program.

Data analytics jobs are on the rise. Career growth for mathematicians and statisticians is expected to increase 31% by the year 2031, according to The U.S. Bureau of Labor Statistics.

In New York City, you'll have access to this growing career field. You can intern either with an established company, or get in on the ground floor in the city's tech startup industry.

After graduation, we're proud of our success in helping students land jobs. To date, data analytics master's students have all secured a job within six months of earning their degree. Many have had jobs lined up even before graduation. 

Flexibility and Time to Completion

Students typically complete this 30-credit program in three semesters, with one internship or research project completed during the summer. Undergraduate College students are able to count six credits of graduate coursework toward both their undergraduate and graduate degrees, which shortens the duration of the program.

Other benefits: 

  • The data analytics masters program can be completed full time or part time.
  • Courses are scheduled in the evenings, and some courses are offered in a hybrid (asynchronous) format to accommodate students who work full time.
  • The program also gives flexibility by allowing students to start in either the fall or the spring semester. 

What Will You Learn?

If you have a quantitative undergraduate degree and have taken Calculus I-II-III, Linear Algebra and Probability, this program provides you with experience in:

  • computational methods
  • applied linear algebra
  • statistical methodology and probabilistic modeling
  • machine learning
  • operations research and non-linear optimization
  • database methods
  • computing and programming environments such as MATLAB, R and Python. 

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

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

See degree requirements

Admissions Requirements

Review the requirements and application process for this graduate program.

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. 

Our graduates have interned and worked at: 

Logo for 1010 DataLogo for UPSLogo for BlackRockLogo for NYSERDALogo for Celonis

Students in the Mathematics department also have been successful in obtaining acceptances into Ph.D. programs in applied mathematics, statistics, and operations research at schools including:

  • Columbia University 
  • Johns Hopkins University
  • Pennsylvania State University
  •  Michigan State University
  • 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.”