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Data specialist vs data scientist

The differences between data specialists and data scientists can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 1-2 years to become a data specialist, becoming a data scientist takes usually requires 2-4 years. Additionally, a data scientist has an average salary of $106,104, which is higher than the $68,326 average annual salary of a data specialist.

The top three skills for a data specialist include data analysis, data entry and data collection. The most important skills for a data scientist are python, data science, and visualization.

Data specialist vs data scientist overview

Data SpecialistData Scientist
Yearly salary$68,326$106,104
Hourly rate$32.85$51.01
Growth rate9%16%
Number of jobs100,301106,973
Job satisfaction--
Most common degreeBachelor's Degree, 56%Bachelor's Degree, 51%
Average age4441
Years of experience24

What does a data specialist do?

A data specialist's role is to process data, transferring them into an electronic platform or database for record-keeping or creating systems. Their primary responsibility is to ensure the accuracy of every inputted data point and verify its authenticity by reaching out to clients or using specific software. There are also instances when they must perform various analyses or take part in different product development processes. Furthermore, it is crucial to be able to identify any anomalies or inconsistencies; this way, corrective measures can be quickly implemented.

What does a data scientist do?

A Data Scientist analyzes information from multiple sources in order to gain maximum insight that can give the company a competitive advantage. They work in different domains, including manufacturing, healthcare, education, and finance.

Data specialist vs data scientist salary

Data specialists and data scientists have different pay scales, as shown below.

Data SpecialistData Scientist
Average salary$68,326$106,104
Salary rangeBetween $40,000 And $116,000Between $75,000 And $148,000
Highest paying CitySan Francisco, CARichmond, CA
Highest paying stateConnecticutCalifornia
Best paying companyMcKinsey & Company IncThe Citadel
Best paying industryManufacturingStart-up

Differences between data specialist and data scientist education

There are a few differences between a data specialist and a data scientist in terms of educational background:

Data SpecialistData Scientist
Most common degreeBachelor's Degree, 56%Bachelor's Degree, 51%
Most common majorBusinessComputer Science
Most common college-Columbia University in the City of New York

Data specialist vs data scientist demographics

Here are the differences between data specialists' and data scientists' demographics:

Data SpecialistData Scientist
Average age4441
Gender ratioMale, 40.6% Female, 59.4%Male, 79.6% Female, 20.4%
Race ratioBlack or African American, 9.6% Unknown, 4.3% Hispanic or Latino, 19.5% Asian, 9.9% White, 56.0% American Indian and Alaska Native, 0.6%Black or African American, 4.2% Unknown, 5.4% Hispanic or Latino, 6.9% Asian, 18.8% White, 64.2% American Indian and Alaska Native, 0.6%
LGBT Percentage5%9%

Differences between data specialist and data scientist duties and responsibilities

Data specialist example responsibilities.

  • Manage the FAA's classify operations program.
  • Manage and prepare pharmaceutical records for multiple FDA audits.
  • Create UNIX and LINUX shell scripts to automate data migration process.
  • Create packages in SSIS to automate importing text files into a data mart.
  • Participate in data profiling activities and lead root cause / impact analysis sessions.
  • Manage offshore developers to support DBA operations.
  • Show more

Data scientist example responsibilities.

  • Update, maintain, and manage regional CRM database and records for customers, vendors, and suppliers.
  • Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
  • Lead the analysis in SAS for data integration of mortality data using meta-analysis integration methods.
  • Implement a proximal stochastic gradient descent with a line search to fit a regularize logistic regression in Scala
  • Perform cross-validation-test on linear regression model of data using scikit-learn.
  • Develop python base statistical visualization to provide insights of fuzzy social media data.
  • Show more

Data specialist vs data scientist skills

Common data specialist skills
  • Data Analysis, 7%
  • Data Entry, 7%
  • Data Collection, 7%
  • Customer Service, 7%
  • Data Management, 6%
  • Visualization, 6%
Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%

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