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Computer and Information Research Scientists

SOC 15-1221.00Job Zone 5 · Extensive Preparationv.26.05

Context coveredThis framework covers the full research and development lifecycle for Computer and Information Research Scientists working across academic, corporate, and government R&D environments, from supervised lab entry through executive-level strategic leadership in computing innovation.

Sources:O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.SkillsCrosswalkSkillsCrosswalk — O*NET enrichment + adjacency index. Opens in new tab.
Emerging
Entry / Apprentice
  1. Computer hardware and software problems — analyze root causes under faculty or senior researcher direction in a university or corporate research lab setting.
  2. Mathematical models of technical problems — formulate with guidance by applying foundational coursework to structured research problems in supervised project work.
  3. Existing theoretical frameworks — review and summarize to support innovation efforts on an assigned research team in an academic or R&D environment.
  4. Development environment software and analytical tools — operate following established lab protocols to run experiments and record results under close supervision.
  5. Technical literature and research proposals — read and synthesize to identify relevant prior work in preparation for team meetings and literature reviews.
  6. Research task priorities — track and report progress against assigned milestones under the direction of a principal investigator or project lead.
  7. Basic programming scripts and algorithms — write and test in a supported codebase environment to implement well-defined research procedures.
  8. Database management and query software — use to retrieve and organize research data sets according to project specifications under supervision.
  9. Multidisciplinary project team meetings — participate in by contributing domain-specific knowledge in areas such as human-computer interaction or robotics.
  10. Oral and written research summaries — prepare and present to supervisors and lab peers to communicate early-stage experimental findings clearly.
Developing
Mid-level / Established
  1. Computer hardware and software design specifications — develop with moderate independence by applying theoretical principles to targeted research problems in a corporate or government lab.
  2. Mathematical and computational models — construct and validate routinely to represent engineering or scientific problems for computer-based solution in familiar research domains.
  3. New technology applications — adapt existing principles to novel uses by conducting structured feasibility analyses on moderately complex research initiatives.
  4. Project plans and proposals — evaluate for technical and resource feasibility using established assessment criteria within a defined research program.
  5. Cross-functional meetings with managers and vendors — facilitate to resolve technical coordination issues and align deliverables on active R&D projects.
  6. Systems analysis techniques — apply to identify performance gaps and improvement opportunities in computing systems operating within a known research environment.
  7. Analytical and scientific software platforms — configure and deploy to process complex data sets and generate reproducible experimental results with limited oversight.
  8. Research task scheduling — manage across multiple concurrent assignments by setting priorities and adjusting timelines to meet project goals in a team setting.
  9. Technical reports and peer-reviewed manuscripts — draft and revise to communicate research methods and findings to scientific and engineering audiences.
  10. Active learning strategies — apply by integrating emerging literature into ongoing research activities to keep methods current within a specialization area.
Proficient
Senior / Expert IC
  1. Novel hardware architectures and software systems — design end-to-end by synthesizing theoretical innovation and applied engineering judgment across the full research lifecycle.
  2. Complex multidisciplinary problems in areas such as virtual reality or robotics — analyze and resolve autonomously by formulating original computational models and experimental designs.
  3. Theoretical expertise — apply to create new technologies or adapt computing principles to previously unsolved problems in high-stakes research or industry environments.
  4. Systems evaluation frameworks — develop and execute to assess whether deployed technologies meet scientific, operational, and organizational performance criteria.
  5. Non-routine feasibility and risk analyses — conduct on research proposals and project plans, delivering authoritative recommendations to senior leadership and funding bodies.
  6. Expert system and business intelligence software — architect and leverage to extract insights from large-scale data in support of strategic research objectives.
  7. Logical analyses of business, scientific, and engineering problems — lead independently by constructing rigorous mathematical representations suitable for computational solution.
  8. Stakeholder consultations with executives, partners, and regulatory bodies — manage to secure cooperation, resolve technical disputes, and maintain project alignment.
  9. Cloud-based and distributed computing environments — design and optimize to support high-performance research workloads requiring scalability and resilience.
  10. Advanced programming and technology design solutions — produce and publish as original intellectual contributions that extend the state of the art in the field.
Advanced
Lead / Principal / Executive
  1. Organizational research strategy and computing innovation roadmap — define and champion by translating long-range scientific vision into funded, executable R&D programs.
  2. New computational paradigms and breakthrough technologies — pioneer by directing teams of researchers to apply original theoretical frameworks to previously intractable problems.
  3. Enterprise-level systems architecture decisions — make with full accountability, balancing technical rigor, resource constraints, and organizational mission at executive scale.
  4. Multidisciplinary research portfolios spanning AI, robotics, and human-computer interaction — oversee and integrate to ensure coherent scientific progress and cross-domain synergy.
  5. Organizational talent and competency development — lead by mentoring junior scientists, designing research apprenticeships, and building institutional knowledge within the discipline.
  6. Strategic partnerships with industry, government, and academic institutions — cultivate and govern to secure resources, expand research influence, and accelerate technology transfer.
  7. Peer-review and editorial leadership in high-impact scientific venues — exercise to shape the direction of the field and uphold rigorous standards for computational research.
  8. Feasibility and investment decisions on large-scale technology initiatives — render by synthesizing inductive and deductive reasoning across complex technical, financial, and policy dimensions.
  9. Organizational innovation culture — foster by setting norms of intellectual curiosity, dependability, and evidence-based experimentation across research divisions.
  10. Policy and standards contributions at national or international level — lead by representing organizational expertise in computing research to shape regulatory and technical frameworks.

AI-at-Work Competency Framework

Sources:Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab.Jadhav & Danve, 2026Skill Automation Feasibility Index — Jadhav & Danve, 2026 (arXiv:2604.06906). Opens in new tab.WEF Skills TaxonomyWEF Skills Taxonomy 2021 — Building a Common Language for Skills at Work. Opens in new tab.

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Pathsmith™ Durable Skills Framework

Sources:Pathsmith™ Durable SkillsPathsmith™ Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
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Source anchors that ground each statement

Related titles
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RAPIDS apprenticeships
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O*NET skills
Judgment and Decision MakingCritical ThinkingComplex Problem SolvingReading ComprehensionActive ListeningSystems AnalysisProgrammingSystems EvaluationActive LearningSpeakingTime ManagementWritingMathematicsOperations AnalysisTechnology DesignMonitoringScienceLearning StrategiesSocial PerceptivenessCoordinationInstructing
Knowledge domains
Computers and ElectronicsMathematicsEngineering and TechnologyEnglish LanguageAdministration and ManagementDesignTelecommunications
Abilities
Inductive ReasoningDeductive ReasoningOral ExpressionOral ComprehensionFluency of IdeasWritten ComprehensionProblem SensitivityWritten ExpressionCategory FlexibilityInformation Ordering
Work styles
Intellectual CuriosityInnovationAttention to DetailAdaptabilityAchievement OrientationDependability
Technology
Graphics or photo imaging softwareDevelopment environment softwareAnalytical or scientific softwareData base management system softwareData base user interface and query softwareCloud-based management softwareExpert system softwareProcedure management softwarePortal server softwareBusiness intelligence and data analysis software
Tasks · seed anchors for statements
  1. Analyze problems to develop solutions involving computer hardware and software.
  2. Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
  3. Assign or schedule tasks to meet work priorities and goals.
  4. Meet with managers, vendors, and others to solicit cooperation and resolve problems.
  5. Design computers and the software that runs them.
  6. Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.
  7. Evaluate project plans and proposals to assess feasibility issues.
  8. Participate in multidisciplinary projects in areas such as virtual reality, human-computer interaction, or robotics.
CIP education codes
11.010111.010211.010311.010411.019911.040111.070111.080411.090226.110330.310130.700130.709940.051251.2706

Sources: O*NET v30.2 (CC BY 4.0), SkillsCrosswalk.com, LER.me®, Anthropic Economic Index, SAFI (Jadhav & Danve, 2026), WEF Skills Taxonomy 2021, Pathsmith™ Durable Skills Framework. © 2026 EBSCOed.