What exactly does a data scientist do?

What exactly does a data scientist do?

What exactly does a data scientist do in simple terms, a data scientist’s job is to analyze data for actionable insights.

Specific tasks include:

• Identifying the data-analytics problems that offer the greatest opportunities to the organization
• Determining the correct data sets and variables
• Collecting large sets of structured and unstructured data from disparate sources
• Cleaning and validating the data to ensure accuracy, completeness, and uniformity
• Devising and applying models and algorithms to mine the stores of big data
• Analyzing the data to identify patterns and trends
• Interpreting the data to discover solutions and opportunities
• Communicating findings to stakeholders using visualization and other means

In the book, Doing Data Science, the authors describe the data scientist’s duties this way:

“More generally, a data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human.What exactly does a data scientist do She spends a lot of time in the process of collecting, cleaning, and munging data, because data is never clean. This process requires persistence, statistics, and software engineering skills—skills that are also necessary for understanding biases in the data, and for debugging logging output from code.

Once she gets the data into shape, a crucial part is exploratory data analysis, which combines visualization and data sense. She’ll find patterns, build models, and algorithms—some with the intention of understanding product usage and the overall health of the product, and others to serve as prototypes that ultimately get baked back into the product. She may design experiments, and she is a critical part of data-driven decision making.What exactly does a data scientist do She’ll communicate with team members, engineers, and leadership in clear language and with data visualizations so that even if her colleagues are not immersed in the data themselves, they will understand the implications.”