Data science is a discipline that combines math, statistics, programming, analytics, AI, and machine learning to find insights in an organization's data. These insights can be used to help with decision making and strategic planning.

Data Scientist

Collects large amounts of data using analytical, statistical, and programmable skills. Data scientists lead research projects to extract valuable information from big data. They are skilled in technology, mathematics, business, and communications. Data scientists are responsible for:

• Collecting and cleaning data
  
• Selecting appropriate analytical techniques
• Deploying models in real-world scenarios
• Constructing questions around specific data sets
• Using data analytics and advanced analytics to find patterns
• Creating predictive models
• Developing insights that guide business decision-making
• Data Engineer

Designs, creates, and manages systems that data scientists use to access and analyze data. Data engineers typically build data models and data pipelines, as well as supervise extract, transform, and load (ETL).

Data Analyst

Uses mathematical and statistical analysis to transform complex datasets into actionable insights that drive business decisions. Data analysts use data visualization tools to communicate their findings to both technical and non-technical stakeholders. Data analysts also bridge the gap between the data scientists and the business analysts, organizing and analyzing data to answer the questions the organization poses.