“A data scientist is someone who can predict the future based on past patterns whereas a data analyst is someone who merely curates meaningful insights from data.”
“A data scientist job roles involves estimating the unknown whilst a data analyst job roles involves looking at the known from new perspectives.”
“A data scientist is expected to generate their own questions while a data analyst finds answers to a given set of questions from data.”
Data Analyst vs. Data Scientist – Differences
- The job role of a data scientist strong business acumen and data visualization skills to converts the insight into a business story whereas a data analyst is not expected to possess business acumen and advanced data visualization skills.
- Data scientist explores and examines data from multiple disconnected sources whereas a data analyst usually looks at data from a single source like the CRM system.
- A data analyst will solve the questions given by the business while a data scientist will formulate questions whose solutions are likely to benefit the business.
- In many scenarios, data analysts are not expected have hands-on machine learning experience or build statistical models but the core responsibility of a data scientist is to build statistical models and be well-versed with machine learning.
- Most Data Scientists / Analysts get productive on their projects by having access to a ready-to-use library of sample solved code snippets