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

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 mining skills along with experience in
handling algorithms and coding

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