Data Scientists

Turning Data into Decisions 

Transform raw data into meaningful insights as a data scientist and Hardin-Simmons graduate. Your career could involve analyzing large datasets, developing predictive models, and reporting key findings to help organizations make informed, data-driven decisions 

What to Expect

110k

$112,590 Median Annual Salary

Bright

New job opportunities are very likely in the future.

N/A

No Data Found.

Programs Related to this Career

Computer Science Degree

BA, BBS, BS

Mathematics Degree

BA, BS

Information Systems Degree

BBA

Your Day to Day

  • Analyze, manipulate, or process large sets of data using statistical software.
  • Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
  • Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
  • Clean and manipulate raw data using statistical software.
  • Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
  • Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
  • Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
  • Design surveys, opinion polls, or other instruments to collect data.
  • Identify business problems or management objectives that can be addressed through data analysis.
  • Identify relationships and trends or any factors that could affect the results of research.
  • Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
  • Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
  • Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
  • Recommend data-driven solutions to key stakeholders.
  • Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
  • Write new functions or applications in programming languages to conduct analyses.

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