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Remote Geospatial Data Scientist Jobs in Raleigh, NC

Archgroup

Manager, Data Engineer (Remote)

Raleigh, NC · Remote

$100K - $174K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

College degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent. For individuals assigned or hired to work in the location(s) indicated ...

Archgroup

Manager, Data Engineer (Remote)

Raleigh, NC · Remote

$100K - $174K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

College degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent. For individuals assigned or hired to work in the location(s) indicated ...

Redhat

Principal Data Engineer

Raleigh, NC · On-site +1

$137K - $203K/yr

S. or foreign equivalent) in Computer Engineering, Computer Science or related field and five (5) ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

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All JobsGeospatial Data Scientist JobsRemote Geospatial Data Scientist JobsRemote Geospatial Data Scientist Jobs in Raleigh, NC

Remote Geospatial Data Scientist information

See Raleigh, NC salary details

$36.5K

$119.3K

$191K

How much do remote geospatial data scientist jobs pay per year?

As of Aug 13, 2026, the average yearly pay for remote geospatial data scientist in Raleigh, NC is $119,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is the difference between Remote Geospatial Data Scientist vs Remote GIS Analyst?

AspectRemote Geospatial Data ScientistRemote GIS Analyst
Required CredentialsBachelor's/Master's in GIS, Geography, Data Science; experience with spatial analysisBachelor's in GIS, Geography, or related field; proficiency in GIS software
Work EnvironmentData analysis, modeling, programming, and spatial data interpretationMapping, data management, spatial data visualization
Employer & Industry UsageTech companies, environmental agencies, urban planningGovernment agencies, utilities, environmental firms
Common Search & ComparisonFocuses on data science and modelingFocuses on mapping and spatial data management

The Remote Geospatial Data Scientist primarily works on advanced spatial data analysis, modeling, and programming to extract insights from geospatial data. In contrast, the Remote GIS Analyst focuses on mapping, data management, and spatial visualization. Both roles require GIS knowledge but differ in their core responsibilities and skill sets.

How do remote geospatial data scientists typically collaborate with multidisciplinary teams across different time zones?

Remote Geospatial Data Scientists often work with professionals in fields like environmental science, urban planning, and software engineering, many of whom may be distributed globally. Effective collaboration relies on clear communication, regular virtual meetings, and the use of shared platforms for data, code, and project management. Flexible scheduling and asynchronous communication tools are key to coordinating across time zones, ensuring that all team members can contribute to project milestones efficiently. Building strong documentation and leveraging collaborative GIS and data platforms further help streamline workflows and maintain project momentum in a remote environment.

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

To thrive as a Remote Geospatial Data Scientist, you need a strong background in spatial analysis, statistics, and programming, typically supported by a degree in geography, computer science, or a related field. Experience with GIS software (such as ArcGIS or QGIS), remote sensing tools, and programming languages like Python or R is essential, along with familiarity with cloud-based data platforms. Strong problem-solving, self-motivation, and effective communication skills are vital for collaborating remotely and turning complex geospatial data into actionable insights. These skills enable professionals to efficiently interpret and analyze spatial data, deliver valuable solutions, and work effectively within distributed teams.

What is a remote geospatial data scientist?

A Remote Geospatial Data Scientist is a professional who analyzes and interprets spatial data, such as maps, satellite imagery, and GPS data, to solve problems or provide insights, all while working from a location outside of a traditional office. They use statistical, mathematical, and programming skills to process large geospatial datasets and often collaborate with teams virtually. Their work can support a variety of industries, including environmental monitoring, urban planning, and logistics, by providing actionable geographic insights. Remote geospatial data scientists commonly use tools like GIS software, Python, and machine learning frameworks. Communication and collaboration tools are also essential for effective remote work.
What are popular job titles related to Remote Geospatial Data Scientist jobs in Raleigh, NC? For Remote Geospatial Data Scientist jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Remote Geospatial Data Scientist jobs in Raleigh, NC look for? The top searched job categories for Remote Geospatial Data Scientist jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Remote Geospatial Data Scientist jobs? Cities near Raleigh, NC with the most Remote Geospatial Data Scientist job openings:
Remote Geospatial Data Scientist jobs near you

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Cary, NC • Remote

$80 - $110/hr

Part-time

Posted 10 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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