data scientist vs data analyst

Data scientist and data analyst have become the hottest job of the 21st century. Most of the people often wonder that “what is the difference between data analyst and data scientist?”

A data scientist is the one who envisages the future based on the past pattern while data analyst is someone who brings significant insights from data. So if you are planning to switch your career to one of these IT blooming field then take a glance at this article to know what differentiates data scientist from a data analyst.

Difference between Data Analyst and Data Scientist

data analytics vs data science

A data scientist should have a good understanding of data visualization and business insights skills to convert the acumen into a business story. On the other side, the data analysts do not need to have data visualization skills and business insights.  Data analyst examines the data from a single source such as CRM system while the data scientist perceives and discovers the data from multiple disconnected sources. Data scientist also prepares questionnaires whose solutions can benefit the business whereas data analyst solves the questions provided by businesses.

Data Scientist vs Data Analyst

Difference between Data Analyst and Data Scientist Skills

Though many people think that the skill set of data analyst and data scientist is almost the same but there is an important difference between these. Data analysts are basically masters in SQL and they use regular expressions to slice and dice the data. On the other hand, data scientists possess good knowledge in analytics, modelling, statistics, computer science and math and even acquainted with the skills of a data analyst. Both data scientist and data analyst know the basic understanding of maths, algorithms, cognizance of software engineering and excellent communication skills but there is a disparity between the skillset of two jobs. Let’s take a look at the tabular structure to have a clear understanding of dissimilarity in their skillset.

Data Scientist Job Responsibilities

  • The main task of data scientist is to explore the new products or functionalities by finding the value of a data.
  • Data scientist performs the data cleaning and processing task by cleansing and organizing data for analysis purpose.
  • They curate machine learning models and new analytical methodologies. Data scientist also discovers a new business that can add value to the organization.
  • Data scientist performs causality experiments by applying epidemiological technique and A/B experiments to recognize the main problems of an experimental result.

Data Analyst Job Responsibilities

  • Data analysts create convention SQL queries to identify patterns and discover correlations from various data points.
  • Data analysts trace and map the data through every system to solve any business problem given to them.
  • They craft and design data reports by utilising reporting tools to assist business executive to make better decisions.
  • Data analysts also coordinate with the engineering team to collect incremental data and even apply statistical analysis.
  • They even explore any data quality partialities and issues in data acquisition.

Data Scientist and Data Analyst Salary

Data Scientist and Data Analyst Salary

The pay scale of data scientists is undoubtedly higher than that of a data analyst. The average salary for the data scientists is $113,436. In the USA and Canada, the median data scientist salary is 122k while data science manager earns an average of $113,436.

On the other hand, the salary of a data analyst is totally dependent upon the type of data analyst profile they are working on. As per survey performed by Bureau of Labor Statistics (BLS), the salary of entry-level data analyst ranges from $50,000 to $75,000 while the experience one gets around $65,000 to $110,000.