Data Scientists

If you are an aspiring data scientist, you must have these top skills.

Data Science is now ruling the world with its different applications among various sectors. It’s now playing a vital role to gain profits. Many youngsters are now showing immense interest in Data Science. Combing with AI in data science, ML in data science and many other technologies Data Scientists are creating wonders and giving results at its best. Data Science is not solely about data but also machine learning, artificial technology, data mining, big data. There are many Data Scientists out there who have many queries regarding what are skills that are required to become data scientist? They have no idea about where to start? From which sources to gather information?  Aspiring to be data scientists might be thinking that data science is a vast field and without any ground work and background it will be difficult to get into the field. To make sure your path is safe here the tops skills that should be known by every data scientist. To become a Data Scientist there are enormous skills which are required and Skills of Data Scientists vary from individual to individual. To know about the top skills of data scientists more read below.

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Top Skills Include:

Knowledge of data visualization tools:

Every data scientist or any individual aspiring to be a data scientist to have basic knowledge about data visualization tools such as Tableau, Qlik, Datameer and others.

Understanding of Programming languages:

Programming Language is a set of instructions or commands used to either write code or to create software programs. Data Scientists should understand and have the knowledge of programming languages such as Python, Java, Java Script, C, C++, MATLAB, SQL and database management systems.

Clarity of Data Analytics Concepts:

Every data scientist should have the clarity of data analytics concepts such as statistics, and deriving the right insights from data.

Should be good at Mathematics:

Math is an integral part of Data Science. Learning math is very much needed in Data Science. Few common types of math that one should learn are linear algebra, calculus, statistics, probability. Applications of math in data science domain includes Natural language processing, computer vision, marketing and sales.

A better understanding of Statistics:

One should need to know statistics in order to become a Data Scientist. Few types of statistics that all should learn include… Descriptive Statistics (mean, median, mode, variance, standard deviation), Inferential Statistics (hypothesis testing, z test, t-test, significance level, p-value), Statistical analysis (linear regression, forecasting, logistic regress).

Statistics play a major role in identifying the importance of features by using various statistical tests. Finding the relationship between features to eliminate the possibility of duplicate features. Converting the features into the required format. Normalizing and scaling the data. This step also involves the identification of the distribution of data and the nature of data. Taking the data for further processing by using required adjustments in the data and many other.

Working with Unstructured Data

Data scientists should know how to work with unstructured data that comes from different channels and sources.

Effective Communication Skills

Data scientist should have an effective communication skill. Data scientists are very good at understanding how to extract, understand, and analyze data. However, if an individual is not good at communicating or expressing the work, he or she has done the entire hard work will go in vain.