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Fall 2015 Career Information Session Retrospective

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Attend the MS in Data Science Admissions FAQ Webinar on January 14th at 9:30am

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NYU Data Science Fellow Brenden Lake Published in Science and Covered in New York Times

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New Data Science Professor Carlos Fernandez-Granda is Tackling Problems in Neuroscience, Computer Vision and Medical Imaging

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Master of Science in Data Science

100% of the graduating class of 2015 were hired in their chosen field.

It's happening in nearly every facet of life, from commerce to utilities.
  • MS in Data Science Candidate

    Rafael Garcia, '17

    "Rafael came to the U.S. to pursue his passion for data science and spent last summer interning as a full-stack web application developer at International Game Technology, in Austin, Texas."

    Student Profiles
  • MS in Data Science Candidate

    Nora Barry, '17

    "A highly motivated individual, Nora is interested in utilizing her analytical and technical skills to solve complex, data-driven problems in business and financial services."

    Student Profiles
  • MS in Data Science

    Urjitkumar Patel, '17

    "After completing his undergrad, Urjit worked at Wipro Technologies as a Data Analyst for two years, and is also an IBM Certified Deployment Professional - Maximo V7.5 Asset Management tool."

    Student Profiles
  • MS in Data Science

    Christina E Bogdan, '17

    "Christina became interested in data science after she started interning at The Weather Channel, where she analyzes large amounts of advertising data."

    Student Profiles
  • MS in Data Science Candidate

    Katrina Evtimova, '17

    "Katrina is interested in conducting data science research focusing on machine learning and the development of new methods for data science and exploring its applications in the IT and financial industries."

    Student Profiles
  • MS in Data Science

    Benjamin Jakubowski, '17

    "Benjamin served as an AmeriCorps*VISTA volunteer in Baltimore and taught 8th grade science in District of Columbia Public Schools."

    Student Profiles
  • MS IN DATA SCIENCE CANDIDATE

    Wenxi Lei, '16

    "Wenxi Lei is the President of the Leadership Circle and received his bachelor's degree from University of Illinois at Urbana-Champaign triple majoring in Statistics, Mathematics (with a Concentration in Operations Research), and Economics."

    Student Profiles

Data science creates meaning from vast amounts of complex data.

Using automated analytical methods, it reveals patterns humans alone might never see. Data science combines aspects of:

Computer
Science

Applied
Mathematics

Statistics

Machine
Learning

Visualization
 

Data science offers new approaches to age-old decision-making and problem-solving processes.

A look at how data science is fundamentally shifting the way professionals do their work:



The Journalist

Databases and visualization software are becoming the newest tools of the trade for investigative journalists. Take for example the The Declassification Engine, a project to sift through a massive amount of declassified U.S. government documents using natural language processing and statistical/machine learning. A group of individuals, let alone an individual journalist, could never reasonably achieve such a feat.

Listen to a member of the project discuss The Declassification Engine

 

The Emergency Services Manager

Cities have long collected and analyzed information about emergency response times, but according to Michael Flowers, director of analytics for New York City’s Office of Policy and Strategic Planning, the information has typically been limited to location. With his office’s help, the city is trying to streamline the emergency response process and get to people in need sooner by looking at a wider range of data elements, such as the operator’s script.

Listen to Michael Flowers talk about the way data is improving NYC

 

The TV/Film Producer

A time-honored way to ensure that a TV program or movie becomes a hit is screening it with test audiences, tweaking the final product in reaction to audience feedback. That’s all changing thanks to online platforms like Netflix that gather information on viewer’s behavior (which episodes are rewatched, at which episode in a series most viewers quit the series, how many minutes into a movie people hit pause) like never before. Such data may change how TV and films are made and distributed. TV and movie makers will have new insight into what audiences like before scripts are shot; producers will be able to target their creations to the individuals that will embrace them most.

Read: "At Netflix, big data can affect even the littlest things"