How can I grow from a data analyst to a data scientist?

Data Analyst and Data Scientist has a lot of roles and responsibilities in common – depending upon the industry or company that the individual is engaged in. However, in general, students need to develop their skillsets and acumen in the field of statistics to make a transition from data analyst to data scientist. Students can scale up in statistics starting from basic probability & algebraic concepts; and then progressing towards more complicated stuffs.
Another important concept which data analyst needs to upskill to become a data scientist is coding, specifically in Python as this is a mandate for developing data science models and algorithms.

Data scientist and data analyst are the same thing called differently in different companies.

What do you use SQL and Excel for? Just making reports? Then you are not really a scientist or an analyst You are, what we call in KSF, a reporting analyst that just takes an order and makes a report with no ad-hoc analysis done to the report.

A data scientist or analyst goes into the details. He/she dives into each column of his data and finds everything that is to find in there. Percentages, shares, distributions, correlations between variables, outliers in 1, 2 or more dimensions, transform your data and look at it again. Really, the tools that you are using don’t matter. What matters is what you use them for.