Skills Required to Kick-Start Your Career in Data Science

Posted on

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.

STATISTICAL LANGUAGES

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 in order to make the provided data sets meaningful.

UNDERSTANDING STATISTICS

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.

MACHINE LEARNING

Dealing with terabytes or petabytes of data, on a daily basis, is very appalling. To deal with them at ease, a data scientist must be familiar with machine learning techniques and methodologies. Having knowledge about k-nearest neighbors, ensemble methods and random forests is of a great advantage. These techniques can be proceeded 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.

MATHEMATICS

To build on your data science skills, you must have a strong foundation when it comes to linear algebra or multivariable calculus. Having a good knowledge in 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.

DATA MINING

Dealing with 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.

DATA VISUALIZATION

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

ANALYTICS

A data scientist must excel at analytical skills like attribution modelling, sales forecasts, mix modelling, 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.

COMMUNICATION SKILLS

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

Leave a Reply

Your email address will not be published. Required fields are marked *