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Remote Computer Science Research Jobs in Arkansas

Data Engineer

Bentonville, AR ยท On-site +1

$100K - $120K/yr

Bentonville AR or Remote Duration: 6 to 12+ Months Rate: DOE Required skills - Spark, Cassandra ... research, and investigation. Experience/Skills Required: 1. Bachelor's degree in Computer Science ...

Guides students through interpreting computer output, checking inference conditions, analyzing two ... social science research, public policy, and medical studies. * Curriculum Awareness & Adaptive ...

Guides students through interpreting computer output, checking inference conditions, analyzing two ... social science research, public policy, and medical studies. * Curriculum Awareness & Adaptive ...

Guides students through interpreting computer output, checking inference conditions, analyzing two ... social science research, public policy, and medical studies. * Curriculum Awareness & Adaptive ...

AP Statistics Tutor

Conway, AR ยท Remote

$40/hr

Guides students through interpreting computer output, checking inference conditions, analyzing two ... social science research, public policy, and medical studies. * Curriculum Awareness & Adaptive ...

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Remote Computer Science Research information

What is the difference between Remote Computer Science Research vs Remote Software Developer?

AspectRemote Computer Science ResearchRemote Software Developer
Required CredentialsAdvanced degrees (Master's/PhD), research experienceBachelor's or higher in CS, coding skills
Work EnvironmentAcademic or research institutions, labsTech companies, startups, freelance projects
Employer & Industry UsageUniversities, research labs, government agenciesSoftware firms, tech industry, consulting
Common Search & Comparison IntentResearch focus, academic rolesDevelopment projects, coding jobs

Remote Computer Science Research typically involves academic or research roles requiring advanced degrees and a focus on theoretical or experimental work. Remote Software Developers focus on building and maintaining software applications, often with coding skills and industry experience. While both roles involve computer science, their work environments, credentials, and industry applications differ significantly.

How do remote computer science researchers typically collaborate with teams and manage project progress?

Remote computer science researchers often collaborate using digital communication platforms such as Slack, Zoom, and collaborative coding tools like GitHub. Regular virtual meetings, shared documentation, and version control systems are essential for synchronizing efforts and tracking project milestones. While working remotely can offer flexibility, it also requires strong self-management and proactive communication to ensure research goals are met and team members stay aligned. Building rapport and maintaining open channels for feedback help address challenges and foster a productive, supportive research environment.

What are the key skills and qualifications needed to thrive as a Remote Computer Science Researcher, and why are they important?

To excel as a Remote Computer Science Researcher, you need advanced knowledge in algorithms, data structures, and research methodologies, often supported by a master's or doctoral degree in computer science or a related field. Familiarity with programming languages (such as Python or C++), version control systems, and collaborative research platforms is typically required. Strong analytical thinking, self-motivation, and effective written communication are vital soft skills for independent work and sharing findings with the research community. These abilities are crucial for producing impactful research, collaborating remotely, and advancing knowledge in the field.

What is remote computer science research?

Remote computer science research involves conducting studies, experiments, or theoretical work in computer science from a location outside of a traditional lab or office setting, typically from home or any place with internet access. Researchers use online collaboration tools, cloud computing resources, and virtual meetings to communicate with team members, access data, and share results. This setup allows for greater flexibility and can broaden participation in research projects across different geographic locations. The work may include areas such as artificial intelligence, cybersecurity, software engineering, or data science, and often requires strong self-motivation and excellent communication skills.
What are popular job titles related to Remote Computer Science Research jobs in Arkansas? For Remote Computer Science Research jobs in Arkansas, the most frequently searched job titles are:
What cities in Arkansas are hiring for Remote Computer Science Research jobs? Cities in Arkansas with the most Remote Computer Science Research job openings:
Infographic showing various Remote Computer Science Research job openings in Arkansas as of June 2026, with employment types broken down into 46% Full Time, 27% Part Time, and 27% Contract. Highlights an 100% Remote job distribution.
Senior Applied Scientist

Senior Applied Scientist

Relativity

Little Rock, AR โ€ข On-site, Remote

Full-time

Medical, Retirement

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Posting Type

Remote/Hybrid

Job Overview

WHO WE ARE Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy, trust, and accountability are critical. Every year, the global justice system benefits from insights generated by Relativity AI across billions of documents. We are just getting started on our journey to use AI to improve the outcome of every discovery, investigation, and analysis performed on our platform. At Relativity, we develop AI guided by our AI Principles. These principles ensure we build AI with clear purpose, empower customers with transparency and control, treat fairness and privacy as first principles, protect customer data by design, and act with a high standard of responsibility and accountability. WHAT WE DO Relativity's AI organization is focused on exploration, experimentation, and turning cutting-edge research into real-world impact. We believe innovation requires experimentation, learning, and iteration. Our teams experiment, evaluate, ship, and learn continuously while maintaining a strong commitment to responsible AI. Applied Science Team The Applied Science team operates at the core of Relativity's AI development. Our team includes specialists with advanced postgraduate training and deep experience building and operating machine learning models at scale. We work closely with engineering, product, design, data engineering, machine learning operations, and LLM engineering teams to translate complex AI research into production-ready features used by legal professionals around the world.

Job Description and Requirements

ABOUT THE ROLE

As a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and machine learning models that power Relativity's next generation of AI-driven product capabilities. You will collaborate closely with applied scientists, engineers, product managers, and designers to build models that help legal professionals organize data, discover the truth, and act on it with confidence.

This role balances research, development, and operational responsibility. You will contribute to Relativity's portfolio of transformational generative AI technologies while adhering to our responsible AI principles and ensuring models perform reliably in real-world, high-stakes environments.

WHAT YOU'LL DO

  • Develop machine learning and generative AI models that ship as customer-facing product features
  • Collaborate closely with engineers to write production-quality code and contribute across the full model deployment lifecycle
  • Design and evaluate models that operate at very large scale, including search and retrieval systems spanning hundreds of millions to billions of documents
  • Contribute to internal standards, processes, and tooling for building, evaluating, and deploying generative AI systems
  • Partner with Product and Data teams to assemble, curate, and synthesize datasets for model development and evaluation
  • Conduct rigorous experimentation, model evaluation, and iteration to improve model quality, explainability, safety, and performance
  • Collaborate across AI, engineering, and product teams to ensure models integrate effectively into larger systems
  • Apply Relativity's AI Principles to ensure responsible, fair, secure, and transparent AI development
  • Communicate complex data science and machine learning concepts clearly and effectively to collaborators with diverse technical backgrounds

WHAT WE'RE LOOKING FOR

Required

  • Experience building search or retrieval systems operating at the scale of hundreds of millions of documents
  • Experience developing and applying generative AI models as part of larger, domain-specific systems
  • Experience across the full machine learning lifecycle, including experimentation, evaluation, deployment, and iteration
  • Experience working in containerized environments using Kubernetes-based tooling and workflows
  • Interest in or experience with the legal industry, eDiscovery, or the broader justice system
  • Strong programming ability in a language such as Python
  • Comfort working in UNIX-based environments using command-line tools
  • Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders

Preferred

  • Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry experience
  • OR Ph.D. in Computer Science or a quantitative field
  • OR the equivalent of 5 years of relevant academic and/or industry experience
  • Experience building and deploying systems that leverage large language models
  • Experience contributing to shared data science or ML engineering standards, tooling, or best practices

WHY WE COULD BE A GREAT FIT

Impactful Mission

  • Your work directly contributes to improving outcomes across the global justice system by helping customers uncover critical insights in massive, complex datasets.

AI at Real Scale

  • You'll work on some of the largest and most complex AI systems in the legal technology market, operating at significant data and computational scale.

Growth and Collaboration

  • You'll collaborate closely with experienced applied scientists, engineers, and product leaders while continuing to grow your expertise in generative AI and production machine learning systems.

Responsible AI Culture

  • You'll be part of an organization deeply committed to building AI that is ethical, transparent, secure, and accountable.

Inclusive Environment

  • We value diverse perspectives, backgrounds, and ways of thinking, and believe they make our teams and products stronger.

Compensation and Benefits

  • Competitive compensation, health and retirement benefits, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, wellness resources, and an equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$146,000 and $218,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models