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Research analyst vs data scientist

The differences between research analysts and data scientists can be seen in a few details. Each job has different responsibilities and duties. While it typically takes 4-6 years to become a research analyst, 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 $70,232 average annual salary of a research analyst.

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

Research analyst vs data scientist overview

Research AnalystData Scientist
Yearly salary$70,232$106,104
Hourly rate$33.77$51.01
Growth rate19%16%
Number of jobs81,374106,973
Job satisfaction4.5-
Most common degreeBachelor's Degree, 70%Bachelor's Degree, 51%
Average age3741
Years of experience64

What does a research analyst do?

A research analyst is responsible for providing a company with insights and advice concerning finance, investments, and expenditures. Utilizing their analytical skills and extensive expertise in marketing, they analyze the trends and significant factors to conclude which decision should be the best to make. They can also take part in conducting an in-depth analysis of a business and examine which areas require improvement or has potential. Furthermore, they may work with a company or independently as a freelance analyst.

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.

Research analyst vs data scientist salary

Research analysts and data scientists have different pay scales, as shown below.

Research AnalystData Scientist
Average salary$70,232$106,104
Salary rangeBetween $45,000 And $107,000Between $75,000 And $148,000
Highest paying CitySeattle, WARichmond, CA
Highest paying stateWashingtonCalifornia
Best paying companyThe CitadelThe Citadel
Best paying industryFinanceStart-up

Differences between research analyst and data scientist education

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

Research AnalystData Scientist
Most common degreeBachelor's Degree, 70%Bachelor's Degree, 51%
Most common majorBusinessComputer Science
Most common collegeUniversity of GeorgiaColumbia University in the City of New York

Research analyst vs data scientist demographics

Here are the differences between research analysts' and data scientists' demographics:

Research AnalystData Scientist
Average age3741
Gender ratioMale, 50.8% Female, 49.2%Male, 79.6% Female, 20.4%
Race ratioBlack or African American, 4.7% Unknown, 4.9% Hispanic or Latino, 11.3% Asian, 14.3% White, 64.7% American Indian and Alaska Native, 0.1%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 Percentage10%9%

Differences between research analyst and data scientist duties and responsibilities

Research analyst example responsibilities.

  • Develop VBA to automate the analysis of website data, which save staff labor time.
  • Manage medication studies, and ensury clinical trial centers conduct studies in accordance with GCP standards.
  • Manage project team meetings using SharePoint calendars.
  • Work with engineering teams to troubleshoot issues.
  • Design and code windows in PowerBuilder for EMPRV application.
  • Assist with ongoing implementation of POS and PC systems for upgrades and new locations.
  • 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

Research analyst vs data scientist skills

Common research analyst skills
  • Data Analysis, 6%
  • Data Collection, 6%
  • Research Projects, 5%
  • PowerPoint, 5%
  • Market Research, 4%
  • Python, 4%
Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%

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