Data Scientist & Data Analyst - what is the difference?

My approach to this question was to analyse data from around 50 current job advertisements in the UK and the US. I looked at the required skills and compared these for data analysts and data scientists.

Summary of findings - differences between data analysts and data scientists

• There wasn't much difference between the skills required of data analysts in the UK and the US, the same was true for data scientist jobs.
• Typical data analyst skills include data mining especially SQL skills and NoSQL skills, data cleansing and data quality, statistics, a degree in a mathmatical subject, working with unstructured data, data visualisation, python or R, data scraping, one skill sometimes quoted which is unique to data analyst is Excel. 
• Data science jobs may include all of the above skills as well as the following: machine learning, algorithms, hadoop, linear algebra, scikit-learn, one or two also mention the need for other programming skills esprcially C++ and Java.
• Data scientists earn about 1.5 to 2.0 times what a data analyst might earn for a similar level job i.e. comparing an entry level Data Analyst job to an entry level Data Science job and so on.
• Many, but not all, employers of data scientists want higher degrees - Masters or PhD whereas Data Analysts usually only require a degree in a mathmatical subject.

My conclusions 

Data Analysts and Data Scientists have similar core skill sets but data scientists require more skills than data analysts. While the skill sets are similar, job roles are less so. Data analyst roles may focus on data quality and obtaining data, possibly generating reports. Data science roles may require more programming skills and will almost certainly involve working with big data rather than just data. The data science roles focus on using the data whereas data analyst roles may focus more on describing/summarising the data. To get the best data science jobs you may need a higher level degree.
​
Other roles that can be similar are Business Intelligence Developer, data quality engineer and data engineer, these may be more technical and may require knowledge of ETL and data warehousing as well as BI tools such as Tableau.