The hottest jobs in tech are mainly data scientists and data analysts. Many students are having a dream of grabbing these job opportunities at the beginning of their careers. Many people often confused with the term data scientist and data analyst, they consider these same. A person engaged in analyzing and infer multifaceted digital data, such as the practice statistics of a website mainly for assisting a business in taking decisions is called a data scientist. The person who is professional and has a focus of scrutiny and problem solving relates to data, types of data along with its relationships among data elements within a business system is called data analyst. Data scientist jobs are very much in demand these days. Here are the 18 differences between a data scientist and a data analyst.

S.No.FeaturesData ScientistData Analyst
1.DefinitionData scientist are the one who gathers structured and unstructured data.Data analyst is the one who collects, processes statistical analyses on the huge data set.
2.Job rolesThere are different job roles like data researchers,   developers, data creative and business people.The different job roles like operations, data architects, database administrators.
3.Data visualization toolsTableauGoogle charts, Tableau, etc.
4.Data sourcesData scientist makes use of multiple data sources for gathering dataData analyst focuses only on the data coming from CRM.
5.Data typeUnstructured and structured dataStructured data
6.SkillsA data scientist is familiar with all the skills that data analyst have along with a great foundation in modeling, mathematics, and statisticsData analyst are the persons who have achieved mastery in SQL
7.Programming languagesHive, Python, R, Scala, MATLAB, SQL, Pig.Python, JavaScript, R, SQL, and HTML.
8.ResponsibilitiesCleaning data

Massaging data

Organizing data


Analyze data

Mine data

Identify patterns


9.Salary PackageSalary ranges between $95000 to $185000Salary ranges between $56043 to $170307
10.TechnicalThey are more technical persons than data analysts. They are a less technical person
11.ApproachThey focus on taking decision belongs to the businessThey focus on decision making
12.Communication skillsThey possess great storytelling and management skills.They don’t generally need
13. TDegreespost-graduate degreeUndergraduate degree in Science, Technology, Education, and Mathematics
14.PreferencesPreference is given to a person who is Ph.D. along with a person from the STEM system  backgroundPh.D. is not mandatory but the STEM system would be there.
15.ExperienceExperienced in scrutinizing data from Google Analytics, AdWords, Facebook Insights, etc.


Experienced in functioning with the agile methodology.
16.Backend softwareSQL and NO SQL for structured and unstructured data.SQL for structured data only.
17.Preferrable softwareExperienced in working with distributed systems.Experienced in Microsoft Office and excel.
18.AlgorithmsML algorithms are used to suit customer needs.Customer-centric algorithm models are preferred according to customer requirements.

In this blog, we have tried to tell the main 18 differences between a data scientist and a data analyst. This blog gives you a wider picture of different career options. Feel free to ask me related queries in the comment section


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