To understand the difference between a business analyst and a data scientist, it is imperative to understand the problems or projects they work on. Let us take up an interesting example. Imagine that you are a manager of a bank and you decide to implement two important projects. You have a team of a data scientist and a business analyst. How will you do the project mapping job? Below are two problem statements:
- Build a business plan to decide how many employees a bank needs to do XXX business in 2021
- Build a model to predict which transaction is Fraudulent
Take your time to understand the problems. What do you think, which problem is best suited for which profile?
The first problem statement requires making several business assumptions and incorporating macro changes into the strategy. This will require more business expertise and decision making, this will be the job of a business analyst.
The second problem statement requires processing vast behavioral data from customers and understanding hidden patterns. For this, the professional should have a very good understanding of problem formulation and algorithms. A data scientist will be a suitable person to tackle this kind of specific and complex problem.