13 Important Skills for Data Scientist

4.            Machine Learning and Deep Learning

Many companies are looking for data scientists to apply machine learning and deep learning to analyze data and discover insights. Skills in these two areas are increasingly important and make data scientists stand out.

5.            Data Wrangling and Data Preparation

These are skills that include overcoming data quality issues and imperfections in data collection. Hence data scientists spend more than 80% of their time preparing data for analysis including profiling, cleaning, and data modeling.

6.            Model Development and Production

Data scientists must be able to choose the right algorithm so that they can use the training data for supervised learning or automatically run algorithms or patterns in unsupervised learning.

7.            Data Visualization

Data scientists need to have this skill in order to highlight and explain the insights they produce, and data visualization is the basic foundation for them. Because a data scientist should understand the use of Tableau, D3.js or various other data visualization tools.

8.            Critical Thinking

The ability to look at data with a skeptical eye can help data scientists reach accurate and unbiased conclusions.

9.            Business Knowledge