Explore Data Science

The amount of data being generated is increasing at a rapid rate with more than 90% of the data in the world being created in just the last few years. This trend is universal and covers every aspect of today’s social, economic, scientific, engineering, civic, and artistic activities. This data holds valuable information that can be used to improve all these activities by either solving existing problems more efficiently or leading to new discoveries, new technologies, and new services. Due to its ability to power innovations, our world today considers data to be the new oil.

Data Science majors possess an extensive set of analytical, computational, and software engineering skills along with strong verbal, written, and visual communication skills in order to realize the value hidden in vast amounts of data, and effectively communicate their findings and solutions.

At the heart of the data scientist is a passion to improve things by leveraging the patterns and information that is often hidden in large amounts of data. Data scientists often start by conceiving a new data-driven solution to an existing problem or an entirely new data-driven service. They proceed to identify the data sources or create new data collection systems in order to obtain the required relevant data. This often involves working with cloud-based “Big Data” infrastructures, designing data collection processes, developing data access APIs, and creating sophisticated data cleaning, extraction, and selection algorithms and processes. Then they use their analytical and programming expertise to explore the space of possible solutions in order to select the appropriate data analysis approaches, implement them on large-scale cloud-based data analysis computing systems, and design robust ways to assess their validity and performance. This often requires a close collaboration and ongoing communication with domain-experts, the end-users of their solutions, and managers.

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What can I do with a major in Data Science?

INDUSTRIES

  • Automotive manufacturing
  • Banking & Finance
  • Construction
  • Consulting
  • Digital communications
  • Education
  • Energy Sector
  • Environmental agencies
  • Finance
  • Gaming
  • Government
  • Healthcare
  • Industrial/food products
  • Information management
  • Insurance
  • Internet
  • Manufacturing
  • Media
  • Medicine & Pharmaceutical
  • Retail
  • Software development
  • Technology
  • Telecommunications
  • Transportation

EMPLOYERS

  • Accenture
  • Amazon
  • Apple
  • Bank of America
  • Boston Scientific
  • Capital One
  • Cognizant Technology Solutions
  • Facebook
  • FICO
  • Google
  • Hewlett-Packard
  • IBM
  • Infosys
  • Intel
  • JPMorgan Chase
  • Medtronic
  • Microsoft
  • Nielsen
  • Oath
  • Oracle
  • Target
  • Tata Consultancy Services
  • Teradata
  • UnitedHealth Group/Optum
  • Wells Fargo

TECHNICAL SKILLS

  • C#
  • C++
  • Classification
  • Cloudera
  • Clustering
  • D3.js
  • Deep Learning
  • Ensemble
  • Methods
  • Excel
  • Java
  • Linux
  • Mac OS
  • Mathematica
  • MATLAB
  • Microsoft
  • Azure
  • MongoDB
  • MotionLab
  • Natural Language Processing
  • Oracle
  • Python
  • R
  • SAS
  • Scala
  • SQL
  • Tableau
  • Unix
  • Visual Basic
  • Windows

POSSIBLE POSITIONS

  • Applications Architect: Track the behavior of applications used within a business and how they interact with each other and with users.
  • Business Intelligence (BI) Developer: Design and develop strategies to assist business users in quickly finding the information they need to make better business decisions. Extremely data-savvy, they use BI tools or develop custom BI analytic application to facilitate the end-users’ understanding of their systems.
  • Data Analyst: Sift through data and provide reports and visualizations to explain what insights the data is hiding. Helps others understand specific queries with charts.
  • Data Architect: Ensure data solutions are built for performance and design analytics applications for multiple platforms.
  • Data Engineer: Perform batch processing or real-time processing on gathered and stored data. Make data readable for data scientists.
  • Data Scientist: Find, clean, and organize data for companies. Data scientists analyze large amounts of complex raw and processed information to find patterns that will benefit an organization and help drive strategic business decisions.
  • Enterprise Architect: Work closely with stakeholders, including management and subject matter experts, to develop a view of an organization’s strategy, information, processes, and IT assets.
  • Infrastructure Architect: Oversee that all business systems are working optimally and can support the development of new technologies and system requirements.
  • Machine Learning Scientist: Research new data approaches and algorithms.
  • Statistician: Interpret, analyze, and report statistical information, such as formulas and data for business purposes.

**Some of these positions may require an advanced degree.

GET INVOLVED

  • Active Energy Club
  • Alpha Sigma Kappa
  • Association for Computing Machinery
  • CSE Ambassadors
  • CSE International Ambassadors
  • Engineers Without Borders
  • Girls Who Code Volunteers
  • National Society of Black Engineers
  • Plumb Bob Honorary Leadership Society
  • Science and Engineering Student Board
  • Society of Asian Scientists and Engineers
  • Society of Hispanic Professional Engineers
  • Society of Women Engineers
  • Solar Vehicle Project
  • Tau Beta Pi
  • TeslaWorks
  • Theta Tau