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Remote Data Science Jobs in Charleston, SC (NOW HIRING)

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

... remote sensing and geospatial data and services. The ideal Geospatial Analyst will be located in ... The successful candidate will serve as a geospatial analyst in OCM's Science and Geospatial ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

... remote sensing and geospatial data and services. The ideal Geospatial Analyst will be located in ... The successful candidate will serve as a geospatial analyst in OCM's Science and Geospatial ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

... remote sensing and geospatial data and services. The ideal Geospatial Analyst will be located in ... The successful candidate will serve as a geospatial analyst in OCM's Science and Geospatial ...

Blackbaud

AI Product Owner - Implement to Renew

SC · On-site +1

$117K - $157K/yr

Act as the connective tissue betweenengineering, data science, UX, security, legal/compliance, and ... Remote-flexible workforce * Wellness Programs * 401(k) program with employer match * Flexible paid ...

Mindgruve

Media Analyst I

Charleston, SC · On-site +1

We are a global digital agency comprised of strategists, creatives, media experts, data scientists ... eligible for remote work. (Bonus points if you're bilingual in Spanish and/or Portuguese ...

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Showing results 21-40

All JobsData Science JobsRemote Data Science JobsRemote Data Science Jobs in Charleston, SC

Remote Data Science information

See Charleston, SC salary details

$22.1K

$98.3K

$187.6K

How much do remote data science jobs pay per year?

As of Aug 14, 2026, the average yearly pay for remote data science in Charleston, SC is $98,301.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,777.00 and $136,347.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote data scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

Can I work remotely as a remote data scientist?

Yes, many remote data scientist positions are available, allowing professionals to work from anywhere with a reliable internet connection. These roles often require skills in programming, data analysis, and familiarity with tools like Python, R, or SQL, and may involve collaboration through online platforms. Remote work arrangements are common in the data science field, especially with the increasing adoption of cloud-based tools and flexible schedules.

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

More about Remote Data Science jobs

What are the most commonly searched types of Data Science jobs in Charleston, SC?

The most popular types of Data Science jobs in Charleston, SC are:

What are popular job titles related to Remote Data Science jobs in Charleston, SC?

For Remote Data Science jobs in Charleston, SC, the most frequently searched job titles are:

What job categories do people searching Remote Data Science jobs in Charleston, SC look for?

The top searched job categories for Remote Data Science jobs in Charleston, SC are:

What cities near Charleston, SC are hiring for Remote Data Science jobs?

Cities near Charleston, SC with the most Remote Data Science job openings:

Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Charleston, SC as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $98,301 per year, or $47.3 per hour.

Senior AI Solutions Architect (Remote Opportunity)

VetsEZ

Charleston, SC • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Job description

VetsEZ is seeking a Senior AI Solutions Architect to lead the design and implementation of enterprise Artificial Intelligence (AI) solutions supporting the Department of Veterans Affairs (VA), with responsibility for AI architecture across the JLV contract. The initial assignment will support the Joint Longitudinal Viewer (JLV) AI Search and Summarization initiative, delivering a secure, governed AI-assisted search and summarization MVP for development, clinical evaluation, and designated-user testing in an approved lower environment utilizing Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) within a secure AWS cloud environment.
Working closely with Government stakeholders, clinical subject matter experts, software engineers, cybersecurity teams, and DevSecOps personnel, this individual will establish the overall AI solution architecture while ensuring scalability, security, interoperability, Responsible AI, and compliance with Federal cybersecurity and AI governance requirements.
Responsibilities:
  • Lead the architecture, design, and implementation of enterprise AI solutions utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
  • Design scalable, secure, and maintainable AI architectures supporting enterprise healthcare applications.
  • Define solution architecture, data flows, system interfaces, AI orchestration, and integration patterns.
  • Evaluate AI technologies, services, and frameworks to support current and future project needs.
  • Ensure architecture supports approved future phases without expanding the authorized MVP scope.
  • Design AI solutions leveraging Amazon Bedrock and AWS cloud services.
  • Architect secure AI pipelines supporting approved document access and processing, retrieval, vector search, prompt orchestration, and AI-assisted summarization.
  • Define strategies for model selection, prompt management, retrieval optimization, and AI performance tuning.
  • Define monitoring and evaluation strategies to detect model, prompt, retrieval, and data drift and address degradation in accuracy, safety, or clinical relevance.
  • Optimize AI architectures for scalability, operational cost, reliability, and response time.
  • Collaborate with DevSecOps teams to support deployment automation and operational readiness.
  • Design integration between AI services and existing enterprise healthcare applications.
  • Define secure interfaces utilizing REST APIs and modern integration patterns.
  • Ensure solutions align with healthcare interoperability standards including FHIR, HL7, and CCD.
  • Collaborate with application development teams to integrate AI capabilities into clinician workflows.
  • Promote consistent architecture patterns and engineering best practices across JLV development teams.
  • Design AI solutions that comply with Federal cybersecurity, privacy, and Responsible AI requirements.
  • Incorporate Human-in-the-Loop (HITL), source traceability, approved data boundaries, retention and purge controls, explainability, auditability, and governance principles into solution architecture.
  • Support Authority to Operate (ATO), AI governance, Security Impact Analysis (SIA), and technology approval activities.
  • Ensure secure handling of Protected Health Information (PHI) and Personally Identifiable Information (PII).
  • Collaborate with cybersecurity teams to implement secure AI architectures and operational controls.
  • Serve as the technical leader for AI architecture across the JLV contract.
  • Mentor software engineers and provide architectural guidance throughout the software development lifecycle.
  • Participate in architecture reviews, design sessions, sprint planning, backlog refinement, and technical estimation.
  • Produce architecture documentation, system design artifacts, interface specifications, and implementation guidance.
  • Present technical approaches and architectural recommendations to Government leadership and stakeholders.

Requirements:
  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Artificial Intelligence, Data Science, or a related technical field, or equivalent experience.
  • 10+ years designing enterprise software solutions.
  • 5+ years designing cloud-native architectures utilizing AWS or comparable cloud platforms.
  • Demonstrated experience architecting Artificial Intelligence, Machine Learning, or Generative AI solutions.
  • Experience implementing enterprise applications utilizing Amazon Bedrock or similar AI platforms.
  • Experience leading technical architecture across multidisciplinary engineering teams.
  • Amazon Bedrock and AWS cloud services
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Prompt engineering, source-grounded AI evaluation, and hallucination testing
  • Vector databases, embeddings, and semantic search
  • REST APIs and enterprise integration
  • Cloud architecture and distributed systems
  • DevSecOps and CI/CD
  • Healthcare interoperability (FHIR, HL7, CCD)

Additional Qualifications:
  • Strong understanding of enterprise architecture principles and cloud-native application design.
  • Experience balancing AI performance, scalability, security, explainability, and operational cost.
  • Excellent analytical, architectural, and problem-solving skills.
  • Strong written and verbal communication skills with the ability to communicate complex technical concepts to diverse audiences.
  • Ability to obtain and maintain a Government Public Trust clearance.
  • Experience supporting the Department of Veterans Affairs (VA), Department of Defense (DoD), or other Federal healthcare organizations.
  • Experience designing AI-enabled clinical workflow, search, summarization, or clinician-support solutions requiring human validation.
  • Knowledge of Responsible AI, NIST AI Risk Management Framework (AI RMF), NIST SP 800-53, FISMA, and FedRAMP, including applicable High-Impact AI requirements.
  • Familiarity with clinical terminology standards including SNOMED CT, ICD-10, RxNorm, and LOINC.
  • AWS Solutions Architect, AWS AI, Machine Learning, or other AWS cloud certifications are highly desirable.

Benefits:
  • Medical, Dental, and Vision Insurance
  • 401(k) with Employer Match
  • Paid Time Off plus Federal Holidays
  • Corporate Laptop
  • Professional Development and Training Opportunities
  • Remote Opportunity

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.
Sorry, we are unable to offer sponsorship at this time.

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