Skills Required to Kick-Start Your Career in Data Science

Skills Required to Kick-Start Your Career in Data Science

Data science has a big impact on today’s world. The field of data science uses mathematics, computer skills and most importantly, statistics. They use methods like machine learning, data mining, visualization, and cluster analysis. It deals with the extraction of the concealed data concerning trends, interpretation, and behavior, to allow decisions to assist the business. The experts who play out the activities are called Data professionals/Data Scientists. According to Harvard, it is the most sought after profession in the world.

Companies use the extracted data and make business decisions. These decisions can help in achieving profits and improve the efficiency of the organization.

Here are the top skills every successful data scientist must possess.


These are the basic tools with which a data scientist must equip himself with. They should be well aware of languages like Python, SQL, and R. Every team must possess skillful scientists who are well versed with these languages to make the provided data sets meaningful.


As a data scientist, understanding statistics is of great importance. He/she should be familiar with distributions, statistical tests, likelihood estimators, etc. They are vital for a data-driven business.


Dealing with terabytes or petabytes of data, daily, is very appalling. To deal with them at ease, a data scientist must be familiar with machine learning techniques and methodologies. Knowing k-nearest neighbors, ensemble methods and random forests are of great advantage. These techniques can proceed with the aid of languages like R and Python libraries. A data scientist must know where to use a particular technique to get the required output.


To build on your data science skills, you must have a strong foundation when it comes to linear algebra or multivariable calculus. Having good knowledge of mathematical calculations is highly required. The small advancements in predictive performance can create an enormous difference. When such data-driven decisions need to be taken, companies can get an advantage over the market competition.


Dealing with an enormous amount of data can get messy. Dealing with imperfections in data like inconsistent string formatting, date formatting, missing data, etc., is of great importance. A skilled data scientist can transform imperfect, messy data into a well managed set of data to obtain insights by applying various data techniques.


Visualization of data is a mixture of science and art. It is considered to be an attractive and essential skill where data-oriented decisions impact the business the most. A good data scientist should be familiar with tools like ggplot and D3.js


A data scientist must excel at analytical skills like attribution modeling, sales forecasts, mix modeling, user profiling, and segmentation, calculating long-time value and many others. Performing data analysis should be from a business point of view, like finance, ROI, marketing, etc.


Companies look for individuals who are proficient with technical terminologies and can explain it to a non-technical person in the easiest way possible. They should be able to transfer technical information to the sales and marketing team.

Source by Shalini M

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