Data Scientist

Overview and Key Facts

What Do They Do?

A data scientist could...

Overview

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Many aspects of peoples' daily lives can be summarized using data, from what is the most popular new video game to where people like to go for a summer vacation. Data scientists (sometimes called data analysts) are experts at organizing and analyzing large sets of data (often called "big data"). By doing this, data scientists make conclusions that help other people or companies. For example, data scientists could help a video game company make a more profitable video game based on players' online behaviors, or help a travel agency figure out what destinations they should make vacation packages for.

Do You Have the Skills and Characteristics of a Data Scientist?

1. Complex Problem Solving: ? Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.
2. Critical Thinking: ? Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.
3. Mathematics: ? Using mathematics to solve problems.
4. Speaking: ? Talking to others to convey information effectively.
5. Active Listening: ? Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times.

6. Active Learning: ? Understanding the implications of new information for both current and future problem-solving and decision-making.
7. Writing: ? Communicating effectively in writing as appropriate for the needs of the audience.
8. Mathematical Communication: ? Explaining mathematical ideas in everyday language.
9. Judgment and Decision Making: ? Considering the relative costs and benefits of potential actions to choose the most appropriate one.
10. Reading Comprehension: ? Understanding written sentences and paragraphs in work related documents.

Core Tasks

Think about if you'd like the typical tasks a Data Scientist might do:

• 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.