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Start the skills you need in your career in data science

2019-04-30 Education No comment

Data science has had a major impact on the world today. The field of data science uses mathematics, computer skills, and most importantly statistics. They use methods such as machine learning, data mining, visualization and cluster analysis. It involves extracting hidden data about trends, interpretations, and behaviors in order to make decisions that help the business. The experts who carry out these activities are called data professionals/data scientists. According to Harvard, it is the most sought after profession in the world.

Companies use extracted data and make business decisions. These decisions help achieve profitability and increase the efficiency of the organization.

Here are the top skills that every successful data scientist must have.

Statistical language

These are the basic tools that data scientists must have. They should be familiar with languages ​​such as Python, SQL, and R. Each team must have skilled scientists who are proficient in these languages ​​to make the data sets provided meaningful.

Understanding statistics

As a data scientist, understanding statistics is very important. He/she should be familiar with distribution, statistical testing, likelihood estimation, etc. They are critical to data-driven business.

Machine learning

Processing terabytes or a few petabytes of data per day is terrible. To handle them easily, data scientists must be familiar with machine learning techniques and methods. Understanding k-nearest neighbors, collection methods and random forests is a big advantage. These techniques can be done in languages ​​such as R and Python libraries. Data scientists must know where to use specific techniques to get the output they need.

mathematics

To build your data science skills, you must have a solid foundation in linear algebra or multivariate calculus. Very good knowledge of mathematical calculations is needed. Small advances in predicting performance can make a huge difference. When this data-driven decision is needed, companies can gain an edge in market competition.

Data mining

Processing large amounts of data can become confusing. Handling defects such as inconsistent string formatting, date formatting, missing data, etc. is very important. Skilled data scientists can transform imperfect, confusing data into well-managed data sets to gain insight by applying various data technologies.

data visualization

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

ANALYTICS

Data scientists must be good at analytical skills such as attribution modeling, sales forecasting, hybrid modeling, user analysis and segmentation, calculating long-term value, and more. Performing data analysis should be from a business perspective, such as finance, ROI, marketing, etc.

Communication skills

The company looks for people who are technically savvy and explains it to non-technical people in the simplest way. They should be able to pass technical information to the sales and marketing team.

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