Data Scientist
A Data Scientist is a person who designs, develops, and deploys algorithms through statistical programming to create a model by creating, analyzing, and interpreting data which will ultimately help in making the business more efficient. But they not only deal with data analysis rather they develop predictive models that use machine learning algorithms that support business-making tools, manage a large amount of data, and create a visualization to aid in understanding.
What are the skills of a Data Scientist?
- Object-oriented programming (OOP)
- Problem-solving
- Python, R, SAS
- SQL (Structured Query Language)
- Machine Learning algorithms
- Analysis data
- Data Visualization
- Communication Skills
Responsibilities of data scientist
- Data preprocessing
- Creating predictive models
- Formulating new test cases for business development
- Fine tuning the machine learning models
- Integrating and storing data.
- Applying Statistical modelling
Difference between Data Scientist and Business Analyst
In today’s world where data is all around everyone relies on data professionals who can analyze and extract data to predict insights from the big data. Data Scientists and Business Analysts are the two main data professionals who deal with data to make informed decisions for organizations. They both handle data to predict insights, and their skills, approaches, and objectives may differ significantly.
In this article, we will explore the main difference between Data Scientists and Business analysts, the skills required, and the responsibilities of both roles.