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Bi developer vs data scientist

The differences between bi developers 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 bi developer and a data scientist. Additionally, a data scientist has an average salary of $106,104, which is higher than the $92,647 average annual salary of a bi developer.

The top three skills for a bi developer include power bi, dashboards and ETL. The most important skills for a data scientist are python, data science, and visualization.

Bi developer vs data scientist overview

BI DeveloperData Scientist
Yearly salary$92,647$106,104
Hourly rate$44.54$51.01
Growth rate21%16%
Number of jobs80,610106,973
Job satisfaction--
Most common degreeBachelor's Degree, 66%Bachelor's Degree, 51%
Average age3941
Years of experience44

What does a bi developer do?

A BI developer, also known as a business intelligence developer, is primarily responsible for designing and implementing different systems that solve and improve business processes and operations. Their responsibilities revolve around coordinating with department personnel to gather accurate data, performing research and analysis, evaluating and improving existing business systems, and conducting regular inspections, providing corrective measures should there be any issues. Moreover, one must generate reports and maintain accurate data of all processes and transactions, in adherence to the company's policies and regulations.

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.

Bi developer vs data scientist salary

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

BI DeveloperData Scientist
Average salary$92,647$106,104
Salary rangeBetween $71,000 And $119,000Between $75,000 And $148,000
Highest paying CitySan Francisco, CARichmond, CA
Highest paying stateWashingtonCalifornia
Best paying companyDropboxThe Citadel
Best paying industryHealth CareStart-up

Differences between bi developer and data scientist education

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

BI DeveloperData Scientist
Most common degreeBachelor's Degree, 66%Bachelor's Degree, 51%
Most common majorComputer ScienceComputer Science
Most common collegeMassachusetts Institute of TechnologyColumbia University in the City of New York

Bi developer vs data scientist demographics

Here are the differences between bi developers' and data scientists' demographics:

BI DeveloperData Scientist
Average age3941
Gender ratioMale, 72.1% Female, 27.9%Male, 79.6% Female, 20.4%
Race ratioBlack or African American, 4.2% Unknown, 4.7% Hispanic or Latino, 7.9% Asian, 34.7% White, 48.2% 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 Percentage8%9%

Differences between bi developer and data scientist duties and responsibilities

Bi developer example responsibilities.

  • Modify several DB2 queries to accomplish the task.
  • Utilize TFS for code check-in and check-out and manage different versions of complicate codes.
  • Manage BO reporting servers for software patches, security upgrades and other maintenance activities.
  • Work with DBA to create jobs, store procedures and triggers in SSMS to automate database updating work.
  • Manage and execute various BO reporting projects within organization.
  • Create sub, drill-down, drill through, parameterize, summary, and matrix reports in SSRS.
  • 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

Bi developer vs data scientist skills

Common bi developer skills
  • Power Bi, 20%
  • Dashboards, 10%
  • ETL, 5%
  • Visualization, 5%
  • SSRS, 5%
  • Data Warehouse, 4%
Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%

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