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Geospatial Data Science Jobs in Oregon (NOW HIRING)

SOSi

Senior Data Scientist

Myrtle Point, OR

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical ...

SOSi

Senior Data Scientist

OR · On-site +1

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical ...

SOSi

Data Scientist

OR · On-site +1

Bachelor's degree in Data Science, Statistics, Computer Science, or a related field, or; * seven ... Knowledge of data visualization, feature selection, and geospatial analytics is required.

SOSi

Data Scientist

Myrtle Point, OR

Bachelor's degree in Data Science, Statistics, Computer Science, or a related field, or; * seven ... Knowledge of data visualization, feature selection, and geospatial analytics is required.

McMillen, Inc.

GIS Specialist

Portland, OR

$50K - $95K/yr

In this role, you'll support scientific and engineering initiatives through cartography, geospatial analysis, data visualization, and spatial data management. Initially, your primary focus will be ...

McMillen, Inc.

GIS Specialist

Portland, OR · On-site

$50K - $95K/yr

In this role, you'll support scientific and engineering initiatives through cartography, geospatial analysis, data visualization, and spatial data management. Initially, your primary focus will be ...

McMillen Inc.

GIS Specialist

Portland, OR · On-site

$50K - $95K/yr

In this role, you'll support scientific and engineering initiatives through cartography, geospatial analysis, data visualization, and spatial data management. Initially, your primary focus will be ...

NV5

GIS Specialist (Multiple Levels)

Portland, OR · On-site +1

Successful candidates will have experience with GIS technologies, geospatial data management ... Natural resources, environmental science, conservation, forestry, wildlife, water resources, or ...

NV5

GIS Specialist (Multiple Levels)

Portland, OR · On-site +1

Successful candidates will have experience with GIS technologies, geospatial data management ... Natural resources, environmental science, conservation, forestry, wildlife, water resources, or ...

NV5

Geospatial Project Manager

Corvallis, OR

Coordination with data acquisition, production, and eGIS teams * Coordination with Account Managers ... Bachelor's degree in business, geography, GIS, science, or engineering program * Master's degree or ...

NV5

Geospatial Project Manager

Corvallis, OR · On-site

Coordination with data acquisition, production, and eGIS teams * Coordination with Account Managers ... Bachelor's degree in business, geography, GIS, science, or engineering program * Master's degree or ...

NV5

Geospatial Project Manager

Corvallis, OR

Coordination with data acquisition, production, and eGIS teams * Coordination with Account Managers ... Bachelor's degree in business, geography, GIS, science, or engineering program * Master's degree or ...

Instacart

Senior Software Engineer, Digital Twin Platform

OR · On-site +1

$122K - $161K/yr

... and data scientists, you will enable sophisticated models and data collection platforms to scale ... Experience with real-time, streaming, or geospatial services and systems in production.

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All JobsGeospatial Data Science JobsGeospatial Data Science Jobs in Oregon

Geospatial Data Science information

See Oregon salary details

$23.3K

$81.9K

$129K

How much do geospatial data science jobs pay per year?

As of Aug 23, 2026, the average yearly pay for geospatial data science in Oregon is $81,934.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,600.00 and $84,600.00 per year, depending on experience, location, and employer.

What is geospatial data science?

Geospatial data science is an interdisciplinary field that focuses on analyzing and interpreting data that has a geographic or spatial component. It combines techniques from data science, statistics, and geographic information systems (GIS) to extract insights, identify patterns, and solve problems related to location-based data. Professionals in this field work with mapping, remote sensing, spatial analysis, and visualization tools to support decision-making in areas like urban planning, environmental monitoring, and logistics.

What are the key skills and qualifications needed to thrive as a geospatial data scientist?

To thrive as a Geospatial Data Scientist, you need a solid background in statistics, spatial analysis, and programming, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases, and coding languages like Python or R is essential, and certifications in GIS can be advantageous. Strong problem-solving skills, attention to detail, and effective communication help translate complex spatial data into actionable insights for diverse stakeholders. These skills ensure accurate data analysis, innovative solutions, and impactful decision-making in fields reliant on geographic information.

How does a geospatial data scientist typically collaborate with other departments or teams within an organization?

Geospatial Data Scientists often work closely with professionals from diverse departments such as urban planning, environmental science, IT, and business analytics. Collaboration usually involves sharing spatial insights, integrating geospatial data with other datasets, and contributing to interdisciplinary projects that require spatial analysis or mapping. Effective communication is crucial, as you'll translate complex geospatial findings into actionable recommendations for non-technical stakeholders. This cross-functional teamwork not only broadens your understanding of organizational goals but also enhances the impact and visibility of geospatial analyses.

What is the difference between Geospatial Data Science vs GIS Analyst?

AspectGeospatial Data ScienceGIS Analyst
Required CredentialsDegree in Data Science, Geography, or related; often includes programming skillsDegree in Geography, GIS, or related; GIS certifications common
Work EnvironmentData analysis, modeling, programming, often in tech or research settingsMapping, spatial data management, using GIS software in various industries
Employer & Industry UsageTech companies, research institutions, government agencies focusing on spatial data analysisUrban planning, environmental agencies, utilities, and government agencies

While both roles work with spatial data, Geospatial Data Science emphasizes data analysis, modeling, and programming skills to extract insights from geospatial data. GIS Analysts focus more on mapping, data management, and using GIS software for spatial analysis. The roles often overlap but differ mainly in technical focus and application areas.

What are the most commonly searched types of Geospatial Data Science jobs in Oregon?

The most popular types of Geospatial Data Science jobs in Oregon are:

What cities in Oregon are hiring for Geospatial Data Science jobs?

Cities in Oregon with the most Geospatial Data Science job openings:

Geospatial Data Science jobs near you
Infographic showing various Geospatial Data Science job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $81,934 per year, or $39.4 per hour.

Senior Data Scientist

SOSi

Myrtle Point, OR

Full-time

Re-posted 5 days ago

Job description

Company Description

Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.

Job Description

SOSi is seeking a Senior Data Scientist to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.

Essential Job Duties:

  • The contractor shall design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes.
  • The contractor shall conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies.
  • The contractor shall submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance.
  • The contractor shall implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements.
  • The contractor shall provide a Rough Order of Magnitude (ROM) Estimate Report before each analytics project, detailing expected Full-Time Equivalent (FTE) hours, compute costs, storage consumption, and infrastructure requirements.
  • The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.
Qualifications
  • Active TS/SCI Clearance.
  • Master’s degree in Data Science, Machine Learning, Statistics, or a related field, or;
    • nine (9) years of equivalent experience in AI/ML model development and deployment. 
  • Personnel must have demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn, integrating models into production environments, and optimizing performance for real-time analytics.
  • Experience with Databricks, Apache Spark, or similar distributed data processing frameworks is required.
  • Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications.
  • Possess the knowledge and capability to develop advanced machine learning models and optimize analytic workflows for predictive and prescriptive intelligence.
  • Proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and feature engineering.
  • Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications is required.
  • Personnel must be able to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data.

Preferred Qualifications:

  • Desirable but not required certifications include Google Professional Machine Learning Engineer, Microsoft Certified: Azure Data Scientist Associate, or TensorFlow Developer Certification.

Additional Information

Work Environment

  • Full remote flexibility.

Working at SOSi

All interested individuals will receive consideration and will not be discriminated against for any reason.