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Definition:<\/strong><\/p>\n A data scientist <\/strong><\/em>is an individual who performs statistical analysis, data mining and data retrieval processes, handling large volume quantities, to identify trends and information relevant to a company.<\/p>\n A data scientist<\/strong> performs data analysis<\/a> with information stored in data warehouses or data centers, in order to solve a variety of business problems, optimize performance, and gather business intelligence<\/a> insights.<\/p>\n\n Data scientists generally analyze large volumes of data. They are always equipped with statistical models and analyze the past together with the current data stored to get recommendations and suggestions for optimal decision making in a business.<\/p>\n These scientists are a fundamental part of the marketing and planning process to identify useful information and obtain statistical data for the planning, execution and monitoring of results-oriented marketing strategies.<\/p>\n The name data scientist is sometimes belittled because it lacks specificity and can be perceived as an aggrandized word referring to the data analyst. In any case, the position is gaining acceptance with large companies that are interested in obtaining meaning from large volumes of data, because of the voluminous amount of structured, unstructured and semi-structured data that a large company produces.<\/p>\n A data scientist possesses a combination of knowledge of analytics, machine learning, data mining, and statistical knowledge, as well as experience with algorithms and coding. Perhaps the most important skill a data scientist possesses, however, is the ability to explain the importance of data in a way that can be easily understood by others.<\/p>\n A Data Scientist is a professional profile that analyzes large volumes of information to extract patterns, build models and support decision-making. It combines statistics, programming, business and communication of results.<\/p>\n<\/details>\n They perform tasks such as cleaning data, exploring datasets, creating predictive models, automating analysis, visualizing results and translating findings into actionable recommendations. They also validate hypotheses and measure model performance.<\/p>\n<\/details>\n The data analyst usually focuses on describing what has happened and generating reports or dashboards. The Data Scientist works with more advanced models, prediction, machine learning and problems of greater technical complexity.<\/p>\n<\/details>\n They provide value through segmentation, churn prediction, attribution, personalization, campaign analysis, forecasting and opportunity detection. Their work helps turn scattered data into more precise business decisions.<\/p>\n<\/details>\n<\/div>\nRoles of Data Scientists<\/h2>\n
Acceptance of the term data scientist<\/h2>\n
Frequently asked questions about Data Scientist<\/h2>\n
\n\nWhat is a Data Scientist?<\/summary>\n
\nWhat functions does a Data Scientist perform?<\/summary>\n
\nWhat is the difference between a Data Scientist and a data analyst?<\/summary>\n
\nHow does a Data Scientist provide value to marketing?<\/summary>\n