Difference between Data Scientist and Data Analyst

“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.”

“A data analyst addresses business problems but a data scientist not just addresses business problems but picks up those problems that will have the most business value once solved.”

“Data analysts are the one who do the day-to-day analysis stuff but data scientists have the what ifs.”

Data analyst and data scientist skills do overlap but there is a significant difference between the two. Both the job roles requires some basic math know-how, understanding of algorithms, good communication skills and knowledge of software engineering.

Data analysts are masters in SQL and use regular expression to slice and dice the data. With some level of scientific curiosity data analysts can tell a story from data. A data scientist on the other hand possess all the skills of a data analysts with strong foundation in modelling, analytics, math, statistics and computer science. What differentiates a data scientist from a data analyst is the strong acumen along with the ability to communicate the findings in the form of a story to both IT leaders and business stakeholders in such a way that it can influence the manner in which a company approaches a business challenge.