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5 Job Skills Every Data Scientist Must Possess

Data Scientists assist in turning raw data into information. An experience in data analytics proves extremely helpful.

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5 Job Skills Every Data Scientist Must Possess

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  1. 5 Job Skills Every Data Scientist Must Possess

  2. Introduction to Data Science • The study of the source of information, what does this information represents and best possible way to turn it into useful resource to develop Business and IT strategies. • Mines large volume of structured or unstructured data to study the patterns that assist enterprises to know market trends, improve efficiencies and become more competitive. • Derive values from data observation and experimentation to validate and derive insights for betterment of the Business

  3. Role of Data Scientists Data Scientists assist in turning raw data into information. An experience in data analytics proves extremely helpful Data Scientist must possess a combination of analytics, statistical, and data miningskills along with experience in handling algorithms and coding

  4. 5 Skills Every Data Scientists Must Possess Understanding of Basic Statistics Machine Knowledge Data Visualization and Communication Using the Basic Tools Software Engineering

  5. Understanding Of Basic Statistics • Familiarity with statistical tests and maximization estimations is one of the important skills. All data-driven companies look forward to work on the data based on the statistical analysis.

  6. Machine Knowledge • Awareness of the Machine Knowledge jargons is a need for becoming an efficient Data Scientist. Some of the terms are k-nearest neighbors, ensemble methods, random forests.

  7. Data Visualization and Communication • The budding companies look for the Data Scientists who are good in Visualizing Data and Communicate well, for helping to make data-driven decisions.

  8. Using the Basic Tools • Every Data Scientist is expected to know the use of basic tools of Data Science. These include the programming languages used to derive statistical data, such as R or Python or SQL as a database query language.

  9. Software Engineering • Having a Software Engineering validation and relevant knowledge also turns helpful while choosing Data Science as a career domain, for implementing the tasks like data logging along with development of the data-driven products.

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