{"schemaVersion":"1.0","exportedAt":"2026-05-15T12:51:29.876Z","occupation":{"soc":"15-1221.00","title":"Computer and Information Research Scientists","group":"Computer & Mathematical","sector":"54","jobZone":5,"jobZoneInferred":false},"framework":{"version":"v.26.05","description":"","contextCovered":"This 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.","levels":{"emerging":{"label":"Emerging","statements":["Computer hardware and software problems — analyze root causes under faculty or senior researcher direction in a university or corporate research lab setting.","Mathematical models of technical problems — formulate with guidance by applying foundational coursework to structured research problems in supervised project work.","Existing theoretical frameworks — review and summarize to support innovation efforts on an assigned research team in an academic or R&D environment.","Development environment software and analytical tools — operate following established lab protocols to run experiments and record results under close supervision.","Technical literature and research proposals — read and synthesize to identify relevant prior work in preparation for team meetings and literature reviews.","Research task priorities — track and report progress against assigned milestones under the direction of a principal investigator or project lead.","Basic programming scripts and algorithms — write and test in a supported codebase environment to implement well-defined research procedures.","Database management and query software — use to retrieve and organize research data sets according to project specifications under supervision.","Multidisciplinary project team meetings — participate in by contributing domain-specific knowledge in areas such as human-computer interaction or robotics.","Oral and written research summaries — prepare and present to supervisors and lab peers to communicate early-stage experimental findings clearly."]},"developing":{"label":"Developing","statements":["Computer hardware and software design specifications — develop with moderate independence by applying theoretical principles to targeted research problems in a corporate or government lab.","Mathematical and computational models — construct and validate routinely to represent engineering or scientific problems for computer-based solution in familiar research domains.","New technology applications — adapt existing principles to novel uses by conducting structured feasibility analyses on moderately complex research initiatives.","Project plans and proposals — evaluate for technical and resource feasibility using established assessment criteria within a defined research program.","Cross-functional meetings with managers and vendors — facilitate to resolve technical coordination issues and align deliverables on active R&D projects.","Systems analysis techniques — apply to identify performance gaps and improvement opportunities in computing systems operating within a known research environment.","Analytical and scientific software platforms — configure and deploy to process complex data sets and generate reproducible experimental results with limited oversight.","Research task scheduling — manage across multiple concurrent assignments by setting priorities and adjusting timelines to meet project goals in a team setting.","Technical reports and peer-reviewed manuscripts — draft and revise to communicate research methods and findings to scientific and engineering audiences.","Active learning strategies — apply by integrating emerging literature into ongoing research activities to keep methods current within a specialization area."]},"proficient":{"label":"Proficient","statements":["Novel hardware architectures and software systems — design end-to-end by synthesizing theoretical innovation and applied engineering judgment across the full research lifecycle.","Complex multidisciplinary problems in areas such as virtual reality or robotics — analyze and resolve autonomously by formulating original computational models and experimental designs.","Theoretical expertise — apply to create new technologies or adapt computing principles to previously unsolved problems in high-stakes research or industry environments.","Systems evaluation frameworks — develop and execute to assess whether deployed technologies meet scientific, operational, and organizational performance criteria.","Non-routine feasibility and risk analyses — conduct on research proposals and project plans, delivering authoritative recommendations to senior leadership and funding bodies.","Expert system and business intelligence software — architect and leverage to extract insights from large-scale data in support of strategic research objectives.","Logical analyses of business, scientific, and engineering problems — lead independently by constructing rigorous mathematical representations suitable for computational solution.","Stakeholder consultations with executives, partners, and regulatory bodies — manage to secure cooperation, resolve technical disputes, and maintain project alignment.","Cloud-based and distributed computing environments — design and optimize to support high-performance research workloads requiring scalability and resilience.","Advanced programming and technology design solutions — produce and publish as original intellectual contributions that extend the state of the art in the field."]},"advanced":{"label":"Advanced","statements":["Organizational research strategy and computing innovation roadmap — define and champion by translating long-range scientific vision into funded, executable R&D programs.","New computational paradigms and breakthrough technologies — pioneer by directing teams of researchers to apply original theoretical frameworks to previously intractable problems.","Enterprise-level systems architecture decisions — make with full accountability, balancing technical rigor, resource constraints, and organizational mission at executive scale.","Multidisciplinary research portfolios spanning AI, robotics, and human-computer interaction — oversee and integrate to ensure coherent scientific progress and cross-domain synergy.","Organizational talent and competency development — lead by mentoring junior scientists, designing research apprenticeships, and building institutional knowledge within the discipline.","Strategic partnerships with industry, government, and academic institutions — cultivate and govern to secure resources, expand research influence, and accelerate technology transfer.","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.","Feasibility and investment decisions on large-scale technology initiatives — render by synthesizing inductive and deductive reasoning across complex technical, financial, and policy dimensions.","Organizational innovation culture — foster by setting norms of intellectual curiosity, dependability, and evidence-based experimentation across research divisions.","Policy and standards contributions at national or international level — lead by representing organizational expertise in computing research to shape regulatory and technical frameworks."]}}},"sources":{"onet":"v30.2 (CC BY 4.0)","crosswalk":"https://skillscrosswalk.com","generator":"LER.me"},"attribution":"© EBSCOed"}