Data Scientists Career Video
Description: Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
Video Transcript
Data scientists use their analytical skills, math knowledge, and statistical software to find answers to complex business and policy questions. They bring new insights and understanding to organizations by analyzing and interpreting data. Data scientists start a project by spending time to understand the specific needs and circumstances of a business decision or need; typical examples include predicting sales, reducing safety hazards, improving staffing plans, refining budgeting processes, and targeting marketing efforts. This understanding guides them to identify the appropriate sets of data for a project; they use different techniques to extract information from large complex data sets and put them into a form that can be analyzed, a practice known as data mining. They may also develop analysis plans with the subject matter experts who need the information. A next step is to clean and analyze the data, often asking different questions of the same data, using statistical analysis software. Then data scientists translate their key data and findings into written reports with graphs, charts, and other data visualizations to ensure their stakeholders understand the results. The work of data scientists takes math skills, computer skills, critical thinking, and creative problem solving. Jobs typically require a bachelor’s degree in mathematics, computer science, data science, or statistics, depending on the position. Some jobs may require a graduate degree in one of those fields. Experience in database design, statistical analysis, data mining, predictive modeling, machine learning, and data visualization are all valuable in this field.