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Quantitative analyst vs data scientist

The differences between quantitative 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 a quantitative analyst and a data scientist. Additionally, a data scientist has an average salary of $106,104, which is higher than the $101,197 average annual salary of a quantitative analyst.

The top three skills for a quantitative analyst include python, SAS and risk management. The most important skills for a data scientist are python, data science, and visualization.

Quantitative analyst vs data scientist overview

Quantitative AnalystData Scientist
Yearly salary$101,197$106,104
Hourly rate$48.65$51.01
Growth rate9%16%
Number of jobs48,644106,973
Job satisfaction--
Most common degreeBachelor's Degree, 53%Bachelor's Degree, 51%
Average age4041
Years of experience44

What does a quantitative analyst do?

A quantitative analyst is trained to gather quantitative methods to help companies do business and make other related decisions. In the world of trading, quantitative analysts are in demand. It is their job as quantitative analysts to help banks value their securities. They identify cost-effective investment opportunities and measure risk. They can also work for the insurance companies to develop pricing models and assess risk evaluation strategies. Also, some quantitative analysts work on the back end to enhance computer software and to evaluate financial data.

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.

Quantitative analyst vs data scientist salary

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

Quantitative AnalystData Scientist
Average salary$101,197$106,104
Salary rangeBetween $68,000 And $148,000Between $75,000 And $148,000
Highest paying CityNew York, NYRichmond, CA
Highest paying stateNew YorkCalifornia
Best paying companyThe CitadelThe Citadel
Best paying industryTechnologyStart-up

Differences between quantitative analyst and data scientist education

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

Quantitative AnalystData Scientist
Most common degreeBachelor's Degree, 53%Bachelor's Degree, 51%
Most common majorFinanceComputer Science
Most common collegeUniversity of Notre DameColumbia University in the City of New York

Quantitative analyst vs data scientist demographics

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

Quantitative AnalystData Scientist
Average age4041
Gender ratioMale, 79.5% Female, 20.5%Male, 79.6% Female, 20.4%
Race ratioBlack or African American, 5.6% Unknown, 4.5% Hispanic or Latino, 7.7% Asian, 14.1% White, 68.0% 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 Percentage7%9%

Differences between quantitative analyst and data scientist duties and responsibilities

Quantitative analyst example responsibilities.

  • Manage and update early engagement processes daily through SharePoint.
  • Develop C++ codes and unix shell scripts in linux environment.
  • Perform extensive data and statistical analysis using advance packages like SAS to provide business solutions.
  • Develop predictive models using logistic regression and CHAID to target existing and prospective customers for catalog mailing events and online campaigns.
  • Create the next generation distribute C++ mortgage analytics library with Intex.
  • Present the visualization of results with Google motion charts and maps to UNDP representatives
  • 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

Quantitative analyst vs data scientist skills

Common quantitative analyst skills
  • Python, 13%
  • SAS, 8%
  • Risk Management, 7%
  • Model Development, 5%
  • Statistical Models, 5%
  • C++, 4%
Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%

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