Skills Needed to Launch Your Career in Data Science

Data science has a huge impact in today’s world. The field of data science uses math, computer skills, and most importantly, statistics. They use methods such as machine learning, data mining, visualization, and cluster analysis. It deals with the extraction of hidden data on trends, interpretation and behavior, to allow decisions to help the business. The experts who carry 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 make profits and improve the efficiency of the organization.

These are the main skills that every successful data scientist must possess.

STATISTICAL LANGUAGES

These are the basic tools that a data scientist must equip himself with. They must have a good knowledge of languages ​​such as Python, SQL, and R. Each team must have skilled scientists who are well versed in these languages ​​for the data sets provided to be meaningful.

UNDERSTANDING THE STATISTICS

As a data scientist, understanding statistics is of great importance. You must be familiar with distributions, statistical tests, probability estimators, etc. They are vital to a data-driven business.

AUTOMATIC LEARNING

Dealing with terabytes or petabytes of data on a daily basis is very scary. To deal with them comfortably, a data scientist must be familiar with machine learning techniques and methodologies. Knowing about k nearest neighbors, ensemble methods, and random forests is a great advantage. These techniques can be performed with the help of languages ​​such as R and Python libraries. A data scientist must know where to use a particular technique to obtain the required result.

MATH

To develop your skills in data science, you must have a solid foundation when it comes to linear algebra or multivariable calculus. It is very necessary to have a good knowledge of mathematical calculations. Small advances in predictive performance can make a huge difference. When data-driven decisions need to be made, companies can gain an advantage over market competition.

DATA PROCESSING

Dealing with a huge amount of data can be difficult. It is of great importance to deal with imperfections in the data such as inconsistent string format, date format, missing data, etc. A trained data scientist can transform imperfect and messy data into a well-managed dataset to gain insights through the application of various data techniques.

DATA VISUALIZATION

Data visualization is a mix of science and art. It is considered an attractive and essential skill where data-driven decisions have the greatest impact on the business. A good data scientist should be familiar with tools like ggplot and D3.js

ANALYTICS

A data scientist must excel in analytical skills such as attribution modeling, sales forecasting, mix modeling, user profiling and segmentation, long-term value calculation, and many others. Performing data analysis should be from a business point of view such as finance, ROI, marketing, etc.

COMMUNICATION SKILLS

Companies are looking for people who are proficient in technical terminology and can explain it to a non-technical person in the easiest way possible. They must be able to transfer technical information to the sales and marketing team.