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 is about the extraction of hidden data on trends, interpretation and behavior, to allow decisions that 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 achieve 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 a data scientist should equip themselves with. They must be highly aware of languages such as Python, SQL, and R. Each team must possess skilled scientists who are well-versed in these languages in order for the data sets provided to be meaningful.
UNDERSTAND 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.
MACHINE LEARNING
Dealing with terabytes or petabytes of data on a daily basis is terrible. To deal with them with 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 a big plus. These techniques can be carried out with the help of languages such as the R and Python libraries. A data scientist must know where to use a particular technique to get the required result.
MATH
To develop your data science skills, you need to have a solid foundation when it comes to linear algebra or multivariable calculus. Having a good knowledge in mathematical calculations is very necessary. Small advances in predictive performance can make a huge difference. When such 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 complicated. Addressing imperfections in the data, such as inconsistent string formatting, date formatting, missing data, etc., is of great importance. A trained data scientist can transform imperfect and messy data into a well-managed dataset for insights by applying 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 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 in analytical skills such as attribution models, sales forecasting, mixed models, user profiling and segmentation, calculating long-term value, and many others. Performing data analysis must be from a business point of view, such as finance, ROI, marketing, etc.
COMMUNICATION SKILLS
Companies are looking for people who are fluent 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.