Geospatial scientist vs staff scientist

The differences between geospatial scientists and staff 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 geospatial scientist and a staff scientist. Additionally, a geospatial scientist has an average salary of $111,782, which is higher than the $93,941 average annual salary of a staff scientist.

The top three skills for a geospatial scientist include GIS, R and python. The most important skills for a staff scientist are data analysis, research projects, and molecular biology.

Geospatial scientist vs staff scientist overview

	Geospatial Scientist	Staff Scientist
Yearly salary	$111,782	$93,941
Hourly rate	$53.74	$45.16
Growth rate	16%	17%
Number of jobs	42,718	121,054
Job satisfaction	-	-
Most common degree	Bachelor's Degree, 60%	Bachelor's Degree, 60%
Average age	41	41
Years of experience	4	4

Geospatial scientist vs staff scientist salary

Geospatial scientists and staff scientists have different pay scales, as shown below.

	Geospatial Scientist	Staff Scientist
Average salary	$111,782	$93,941
Salary range	Between $74,000 And $168,000	Between $63,000 And $137,000
Highest paying City	-	Redwood City, CA
Highest paying state	-	California
Best paying company	-	Etsy
Best paying industry	-	Technology

Differences between geospatial scientist and staff scientist education

There are a few differences between a geospatial scientist and a staff scientist in terms of educational background:

	Geospatial Scientist	Staff Scientist
Most common degree	Bachelor's Degree, 60%	Bachelor's Degree, 60%
Most common major	Geography	Chemistry
Most common college	University of California, Berkeley	Duke University

Geospatial scientist vs staff scientist demographics

Here are the differences between geospatial scientists' and staff scientists' demographics:

	Geospatial Scientist	Staff Scientist
Average age	41	41
Gender ratio	Male, 81.0% Female, 19.0%	Male, 67.8% Female, 32.2%
Race ratio	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%	Black or African American, 6.2% Unknown, 4.1% Hispanic or Latino, 9.4% Asian, 26.5% White, 53.6% American Indian and Alaska Native, 0.1%
LGBT Percentage	9%	8%

Differences between geospatial scientist and staff scientist duties and responsibilities

Geospatial scientist example responsibilities.

Develop and implement tools in both IDL/ENVI and Erdas to automate preprocessing and enhancement of imagery data for exploitation and interpretation.
Test multiple HSI detection algorithms against hundreds of different camouflage schemes and materials.
Compare the performance of multiple HSI detection algorithms to detect and discriminate among different camouflage schemes and materials.
Develop probabilistic models of disease progression to predict future healthcare utilization and capitation revenue.
Communicate defects, encounter during regression test and followed-up with developers until all issues are resolved.
Require to acquire geospatial information and extract essential elements from a wide array of multi-intelligence data to include Sigint and Masint.

Staff scientist example responsibilities.

Lead efforts to replace a critical radioactive immunoassay with a non-radioactive format to measure clinical samples.
Manage clinical sample testing using MSD and ELISA in LIMS, including data review and approval using LIMS.
Assist in managing and maintenance of HPLC and Prep-HPLC systems to ensure maximum productivity for the process development group.
Manage pediatric dose development project, technology transfer project and alternate API supplier qualification project on budget and on schedule
Assist with RNA and DNA extractions from FFPE tissue and blood.
Supervise temps performing HPLC assays and validations during development and production campaigns under GMP conditions.

Geospatial scientist vs staff scientist skills

Common geospatial scientist skills

GIS, 36%
R, 35%
Python, 15%
Visualization, 14%

Common staff scientist skills

Data Analysis, 9%
Research Projects, 7%
Molecular Biology, 5%
Next-Generation Sequencing, 4%
Statistical Analysis, 4%
RNA, 4%