Computational Data Science Job Description

What does a Computational Data Scientist do?

The world is awash in data and it is growing at a mammoth pace. Over 2.5 million trillion byes of data are generated every day. In every minute Uber has 45,000 trips, 456,000 tweets are sent, and 3.6 million Google searches occur. NASA alone generates 121 terabytes of data every single day. It is the job of the data scientist to bring order to the chaos on terabytes of data. A data scientist extracts meaning from data. They search for hidden models, train intelligent systems, create visualizations, identify patterns and trends, and discover solutions and opportunities. The Computational Data Science program prepares students for careers applying and developing tools that support the data needs of tomorrow, from the intelligence in self-driving vehicles to business intelligence systems to opportunities not yet foreseen.

Common tasks that a Computational Data Scientist will perform include:

  • Collecting and categorizing large datasets
  • Cleaning and validating data to ensure accuracy, completeness, and uniformity
  • Identifying patterns and trends
  • Devising models and algorithms to uncover hidden meaning
  • Forecasting future trends and results
  • Training intelligent systems
  • Producing summarizations and visualizations of datasets
  • Communicating results to stakeholders

Is there a high demand for Computational Data Scientists?

The opportunities for Data Scientists are vast and rapidly expanding. Starting salaries reflect the current shortage of qualified data professionals.. A diverse range of businesses are seeking qualified graduates including:

  • Online companies such as Google, Microsoft, Amazon, Twitter, and LinkedIn
  • Computer technology companies such as IBM, Apple, and Oracle
  • Communications companies such as Verizon and T-Mobile
  • Mobile app developers such as Spotify, Shutterfly and Uber
  • Service businesses ranging from insurance to finance such as SAP, Bank of America, and Deloitte
  • Data science companies such as SAS, Palantir, Pixar, and Teradata
  • Product designers and manufacturers such as Intel, General Motors, Nike, Boeing

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