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Analyst vs data scientist

The differences between analysts and data scientists can be seen in a few details. Each job has different responsibilities and duties. It typically takes 2-4 years to become both an analyst and a data scientist. Additionally, a data scientist has an average salary of $106,104, which is higher than the $73,007 average annual salary of an analyst.

The top three skills for an analyst include customer service, troubleshoot and data analysis. The most important skills for a data scientist are python, data science, and visualization.

Analyst vs data scientist overview

AnalystData Scientist
Yearly salary$73,007$106,104
Hourly rate$35.10$51.01
Growth rate11%16%
Number of jobs253,138106,973
Job satisfaction--
Most common degreeBachelor's Degree, 67%Bachelor's Degree, 51%
Average age4441
Years of experience44

What does an analyst do?

Analysts are employees or individual contributors with a vast experience in a particular field that help the organization address challenges. They help the organization improve processes, policies, and other operations protocol by studying the current processes in place and determining the effectiveness of those processes. They also research industry trends and data to make sound inferences and recommendations on what the company should do to improve their numbers. Analysts recommend business solutions and often help the organization roll out these solutions. They ensure that the proposed action plans are effective and produce the desired results.

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.

Analyst vs data scientist salary

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

AnalystData Scientist
Average salary$73,007$106,104
Salary rangeBetween $53,000 And $99,000Between $75,000 And $148,000
Highest paying CityJersey City, NJRichmond, CA
Highest paying stateNew JerseyCalifornia
Best paying companyThe CitadelThe Citadel
Best paying industryTechnologyStart-up

Differences between analyst and data scientist education

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

AnalystData Scientist
Most common degreeBachelor's Degree, 67%Bachelor's Degree, 51%
Most common majorBusinessComputer Science
Most common collegeNorthwestern UniversityColumbia University in the City of New York

Analyst vs data scientist demographics

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

AnalystData Scientist
Average age4441
Gender ratioMale, 52.4% Female, 47.6%Male, 79.6% Female, 20.4%
Race ratioBlack or African American, 7.4% Unknown, 4.4% Hispanic or Latino, 8.5% Asian, 14.3% White, 65.2% American Indian and Alaska Native, 0.2%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 Percentage12%9%

Differences between analyst and data scientist duties and responsibilities

Analyst example responsibilities.

  • Manage support incidents and mitigate customer issues meeting or exceeding establish SLA's.
  • Manage database including all ETL procedures, optimize SQL query to build an online sales platform.
  • Lead the requirement gathering effort from key customers for development of new JAVA applications and for troubleshooting customer issues.
  • Provide hands-on technical support and managing custom software, windows base systems, networking solutions, and database systems.
  • Initiate and lead quality improvement projects to address KPIs such as production, error rate, and turnaround time.
  • Help develop and handle both on and offsite SEO solutions as well as managing local campaigns and international SEO efforts.
  • 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

Analyst vs data scientist skills

Common analyst skills
  • Customer Service, 13%
  • Troubleshoot, 6%
  • Data Analysis, 6%
  • Management System, 5%
  • Project Management, 5%
  • Strong Analytical, 4%
Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%

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