In Data Science there are two career paths, one is Data scientist and other, Data analyst. These are two different job roles but related and falls under same science but what makes them different is the scope of work and the job tasks. Both positions handling data but at different levels and directions, if we separate them into tasks both have different tasks, in few cases overlapping each other, that’s why sometimes it easy to confuse them with each other.
This article will try to explain through day-to-day tasks, job scope and skills needed for them, so it may help if you are trying to find a career path in any of them.
Comparing both of the positions, we find more job openings for Data Analyst and it’s easier to move into a Data analysts’ job because you're expected to have a master's degree in a lot of cases if it is for a data analyst role PhD is not one of the requirements, on the contrary a Data scientist should be a PhD. There are a lot of data analysts who have taken boot camps certificates online courses as well as bachelor’s and master’s degree to enter the field.
Usually, data analytics often building tangible things for example Dashboards, graphs and charts with a better understanding of the scope of work and as a Data Scientist, you're often doing Advanced statistics and building models and using machine learning, and work tends to be research focused where there is no tangible output, and hard to show the value of your work.
Tasks of Data Scientist
Tasks of Data Scientist
Finding patterns in large datasets.
Training machine learning models.
Deploying AI applications.
Tools and Skills for Data Scientist
Machine learning
Coding in Python & R Language
Understanding big Data Platforms, Hadoop or Apache Spark
Database knowledge and SQL
Good communication and problem-solving skills.
Good business understanding.
Advanced statistics linear algebra calculus.
ETL to extract data using the tools like Jupiter Notebook, Google collab notebooks.
Tasks of Data Analyst
Querying Datasets
Interpreting Datasets
Visualizing Datasets
Conceptualize a Datasets
Predictive analytics
Identify trends, correlations and
Forecasting
Prescriptive, Predictive and Diagnostic analytics
Tools and Skills for Data Analyst
Excel Google Sheets, for Visualization tableau. Power BI and ETL.
Basic statistics, Descriptive Statistics, foundational Mathematics
Good communication analytical skills problem-solving skills.
Data Scientist
Tools & Skills
Machine learning
Finding patterns in large datasets.
Python & R Language
Coding in Python & R Language.
AI
Training machine learning models and deploying AI applications.
Data Analyst
Tools & Skills
SQL, Tableau, BI Tools
Excel Google Sheets, for visualization tableau. Power BI and ETL.
Forecasting & Charts
Data analyst is expected to know SQL a bit of python.
Trends & correlations
Basic statistics, Descriptive Statistics, foundational Mathematics.