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Spatial Data Science Jobs in Portland, OR (NOW HIRING)

Skilled at teaching geographic model application, spatial data analysis, and free-response question ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

Scientist - Endometrial Biology

Portland, OR · On-site

$37.50 - $47/hr

We operate at the intersection of biology, engineering, and computational science, building ... Analyze and interpret molecular, imaging, and functional data to generate mechanistic insight and ...

Scientist - Endometrial Biology

Portland, OR · On-site

$37.50 - $47/hr

We operate at the intersection of biology, engineering, and computational science, building ... Analyze and interpret molecular, imaging, and functional data to generate mechanistic insight and ...

Deep knowledge of physical geography, human geography, map reading and spatial analysis, climate ... Guides students through reading topographic and thematic maps, analyzing population data and ...

Senior Research Analyst

Portland, OR · On-site

$123K - $123K/yr

They may possess specialized skills, such as spatial analysis or statistical analysis. This ... data and sources of information that are appropriate to assigned tasks. • Ensures that data and ...

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Spatial Data Science information

See Portland, OR salary details

$47.2K

$137.6K

$188.2K

How much do spatial data science jobs pay per year?

As of Jul 1, 2026, the average yearly pay for spatial data science in Portland, OR is $137,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,400.00 and $145,800.00 per year, depending on experience, location, and employer.

What is the highest paying GIS job?

The highest paying GIS jobs are often senior roles such as GIS Director, Geospatial Data Scientist, or GIS Manager, with salaries exceeding $100,000 annually. These positions typically require advanced skills in spatial analysis, programming, and leadership, and may involve working with tools like ArcGIS, Python, or SQL.

What is spatial data science?

Spatial data science is a field that combines data science techniques with geographic information systems (GIS) to analyze and interpret spatial or location-based data. It involves collecting, processing, and visualizing data that has a geographic or spatial component, such as maps, satellite images, or GPS coordinates. Spatial data scientists use methods from statistics, machine learning, and computer science to solve problems related to urban planning, environmental monitoring, transportation, and more. The insights gained from spatial data science help organizations make better decisions based on the relationships and patterns found in geographic data.

Is GIS hard to get a job in?

Getting a job in GIS or spatial data science can be competitive, but having strong skills in GIS software like ArcGIS or QGIS, programming languages such as Python or R, and a solid understanding of spatial analysis can improve employability. Relevant certifications and a portfolio of projects also enhance job prospects in this field.

What are the key skills and qualifications needed to thrive as a Spatial Data Scientist, and why are they important?

To thrive as a Spatial Data Scientist, you need a strong background in statistics, geospatial analysis, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases (like PostGIS), and relevant certifications (e.g., Esri Technical Certification) is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication are vital soft skills to interpret spatial data and convey insights to stakeholders. These competencies are crucial for extracting actionable insights from complex geospatial datasets and supporting informed decision-making.

Is 40 too late for data science?

Age is generally not a barrier to entering a data science or spatial data science career, as skills and experience are more important. Many professionals successfully transition into data science later in life by acquiring relevant skills such as programming, statistics, and data visualization, often through online courses or certifications. Employers value diverse experiences, and continuous learning can help you stay competitive regardless of age.

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

AspectSpatial Data ScienceGeospatial Analyst
Required CredentialsDegree in GIS, Geography, Data Science, or related fields; often includes certifications in GIS or data analysisDegree in Geography, GIS, or related fields; certifications in GIS software are common
Work EnvironmentData analysis, modeling, and programming; often in tech or research settingsMapping, data visualization, and GIS software use; typically in government, environmental, or urban planning agencies
Employer & Industry UsageTech companies, research institutions, urban planning, environmental agenciesGovernment agencies, environmental consultancies, urban planning firms

Spatial Data Science focuses on analyzing spatial data using advanced data science techniques, programming, and modeling. In contrast, Geospatial Analysts primarily work with GIS software to create maps and visualize spatial data. While both roles require GIS knowledge, Spatial Data Scientists often have stronger programming and statistical skills, working on complex data analysis projects, whereas Geospatial Analysts focus more on mapping and data visualization tasks.

Is GIS a high demand job?

GIS (Geographic Information Systems) professionals, including those in spatial data science, are in high demand across industries such as urban planning, environmental management, and transportation. The growing use of spatial analysis, remote sensing, and GIS software like ArcGIS and QGIS contributes to strong job prospects and competitive salaries in this field.

What are some typical challenges spatial data scientists face when integrating geospatial data from multiple sources?

Spatial data scientists often encounter challenges like inconsistencies in data formats, varying coordinate reference systems, and differences in spatial resolution when integrating geospatial data from multiple sources. Addressing these requires familiarity with data transformation tools and a strong understanding of spatial data standards. Additionally, ensuring data quality and managing large datasets can be complex, so attention to detail and effective use of GIS software are crucial for successful integration.
What job categories do people searching Spatial Data Science jobs in Portland, OR look for? The top searched job categories for Spatial Data Science jobs in Portland, OR are:
What cities near Portland, OR are hiring for Spatial Data Science jobs? Cities near Portland, OR with the most Spatial Data Science job openings:
Computational Biologist 3

Full-time

Posted 11 days ago


Oregon Health & Science University rating

8.1

Company rating: 8.1 out of 10

Based on 94 frontline employees who took The Breakroom Quiz

134th of 544 rated colleges and universities


Job description

Department Overview

The OHSU Knight Cancer Institute, known as one of the pioneers in personalized cancer medicine, is an international leader in research and cancer treatment. Driven by its mission to end cancer as we know it, the institute is building upon its expertise in targeted treatments to advance the early detection of cancer when the disease is most treatable.

Function/Duties of Position

This position serves as a scientific and operational partner supporting the analysis, interpretation, and translation of complex cancer research datasets across Knight Cancer Institute programs. This position will have two primary functions:

  • To lead analysis and mining of critical datasets associated with Knight Cancer Institute strategic initiatives, including resources generated through the Brenden-Colson Center for Pancreatic Care (BCC), in order to accelerate translation, increase usability, and expand impact across Knight Cancer Institute;
  • To implement new analytical workflows, service models, and training approaches within the Cancer Data Science Shared Resource (CDSSR) to ensure emerging Knight Cancer Institute needs are met, including single-cell and spatial omics applications.
  • This position will be responsible for managing timelines and communications needed for successful progression of  Knight data science needs. This role acts as a key interface between Knight Cancer Institute scientists, shared resource staff, and Knight Cancer Institute leadership, translating scientific priorities into scalable computational solutions and practical operational processes. Work is guided through regular engagement with BCC, Knight Cancer Institute, CDSSR and other leadership and is expected to include development, validation, documentation, and communication of reproducible analysis workflows and custom analytical approaches. This position will engage stakeholders and is responsible for soliciting and disseminating ongoing feedback to positively impact the direction and quality of collaborative relationships.

    Key responsiblities: 

    • Lead analysis and mining of high-value cancer research datasets (including BCC and other critical Knight Cancer Institute datasets) to improve translational relevance, usability, and impact across Knight Cancer Institute
    • Work closely with BCC and Knight Cancer Institute leadership among others to prioritize analyses, and define scientific and operational needs
    • Implement, validate and document computational workflows within the Cancer Data Science Shared Resource (e.g., single-cell, spatial omics, etc).
    • Create and deliver trainings, user guidance, and onboarding materials that improve adoption of new workflows and strengthen investigator and staff capability in advanced cancer data science methods
    Required Qualifications

    Education and experience:

    PhD in Computational Biology, or a related field; OR

    Master's Degree in Computational Biology or related field AND6 years of relevant experience; OR

    Equivalent combination of Bachelor's in relevant field in conjunction with training and experience may be considered.

    Knowledge, skills, and abilities: 

    • Ability to analyze complex biological or biomedical datasets and translate findings into usable outputs for research or translational teams
    • Ability to develop, implement, and document reproducible computational workflows or analytical pipelines in a collaborative scientific environment
    • Ability to work directly with investigators, experimental scientists, shared resources, or research leadership to gather requirements and interpret analysis results.
    • Demonstrated knowledge of modern computational methods relevant to cancer data science, including high-dimensional omics data analysis
    • Must be technically proficient in programming, computational biology and bioinformatics Ability to take initiative, prioritize tasks, work independently, use good judgment and monitor completion of project tasks.
    • Strong written and verbal communication skills, with the ability to explain computational concepts and results to technical and non-technical audiences
    • Ability to work independently and as part of a team while being collaborative in resolving problems
    • Must possess energy and drive to prioritize and coordinate multiple projects simultaneously
    • Ability to use tact and diplomacy to maintain effective working relationships
    Preferred Qualifications
    • Degrees in Bioinformatics, Data Science, Biostatistics, Computer Science, Genomics preferred

    • PhD with direct focus on computational biology with experience omic workflows
    • Experience with cancer-focused data analysis, translational science, or biomedical research programs in an academic health center, cancer center, or comparable environment
    • Strong project management and organizational skills, including the ability to manage multiple priorities and advance work through cross-functional partnerships
    • OHSU RCR, HIPPA and respect, laboratory and general safety education. RCR for Human subjects.
    Additional Details

    #knightinternal #knightcancerjobs 

    Why apply to OHSU?We are Oregon's only public academic health center. In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. As Portland's largest employer, we give you opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington. All are welcome. OHSU welcomes people of all ages, ethnicities, genders, national origins, religions and sexual orientations. We are striving to build an anti-racist, multicultural institution and encourage people with diverse backgrounds to apply. To request reasonable accommodation, contact askhr@ohsu.eduEmployment Type: FULL_TIME

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    About Oregon Health & Science University

    Sourced by ZipRecruiter

    Oregon Health & Science University (OHSU) is a distinguished institution under the industry of higher education and healthcare, specifically in the field of medical science. Based in Portland, Oregon, US, it maintains a reputation for promoting research, teaching, patient care, and outreach. Established in 1887, OHSU has continually sought to redefine the parameters of healthcare delivery and biomedical discovery through its expansive catalog of programs and initiatives. A galvanizing mission drives OHSU: to improve the health and quality of life for all Oregonians through excellence, innovation, and leadership in health care, education, and research.

    Industry

    Colleges, universities, and professional schools

    Company size

    10,000+ Employees

    Headquarters location

    Portland, OR, US

    Year founded

    1887