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Statisticians

SOC 15-2041.00Job Zone 5 · Extensive Preparationv.26.05

Context coveredThis framework covers statisticians working across applied research, government, healthcare, policy, and industry settings who design studies, analyze complex data, and communicate quantitative findings to diverse stakeholders.

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. Descriptive statistics and summary measures — compute and interpret under faculty or senior statistician guidance on assigned research datasets.
  2. Raw data files — organize, check for inaccuracies, and apply basic weighting procedures in preparation for processing on a research project team.
  3. Standard statistical software packages — execute pre-specified analyses and document outputs under direct supervision in an academic or applied research setting.
  4. Statistical tables, charts, and graphs — construct using spreadsheet or analytical software to present findings in structured internal reports.
  5. Sampling concepts and experimental designs — recognize and describe their appropriate application when reviewing existing study documentation.
  6. Research literature and statistical methods sections — read and summarize to support senior statisticians evaluating validity of published procedures.
  7. Relationships and trends in structured datasets — identify using guided exploratory analysis techniques within familiar data environments.
  8. Database query tools — retrieve and filter data from established repositories following documented protocols on a research or consulting team.
  9. Mathematical reasoning — apply foundational probability and inference concepts to verify calculations reviewed by a supervising statistician.
  10. Preliminary findings — present verbally to immediate project team members using prepared slide decks under direction from a project lead.
Developing
Mid-level / Established
  1. Statistical analysis plans — develop and execute routinely for moderately complex studies, adapting methods to meet user needs with limited oversight.
  2. Data quality and preprocessing pipelines — design and apply weighting, imputation, and adjustment procedures independently for standard research datasets.
  3. Validity and efficiency of statistical procedures — evaluate and document for ongoing projects, flagging methodological concerns to senior staff.
  4. Regression, ANOVA, and multivariate techniques — implement and interpret across familiar applied contexts including government, healthcare, or industry settings.
  5. Graphs, charts, and written reports — produce to communicate statistical results clearly to technical and semi-technical audiences in a professional environment.
  6. Sampling frame design and sample size determination — execute for survey or experimental studies using established methodological references.
  7. Statistical programming scripts — write and maintain in R, Python, or SAS to automate recurring analytical workflows within a departmental setting.
  8. Relationships and confounding factors in research data — identify and interpret, providing documented explanations of trends affecting study conclusions.
  9. Client or stakeholder meetings — present statistical findings using charts and bullets, responding to moderately complex questions with confidence.
  10. Business intelligence and data mining tools — apply to extract and synthesize patterns from large organizational datasets in support of ongoing projects.
Proficient
Senior / Expert IC
  1. Complex multivariable and longitudinal statistical models — design, validate, and interpret autonomously across diverse research domains including clinical trials, policy analysis, and industrial applications.
  2. Full-scope data preparation workflows — architect and execute for large-scale or non-standard datasets, resolving inaccuracies and structural anomalies without supervisory input.
  3. Statistical methodology selection — evaluate and justify the most appropriate techniques for novel user needs or research questions, drawing on breadth of theoretical and applied knowledge.
  4. Non-routine methodological challenges — diagnose and resolve, including violations of model assumptions, missing data patterns, and small-sample inference problems in real project environments.
  5. Comprehensive analytical reports — author for senior leadership, regulators, or peer-reviewed publication audiences, integrating statistical and contextual findings with precision and clarity.
  6. Experimental and quasi-experimental designs — develop and test end-to-end, including power analysis and adaptive design modifications, in research or operational settings.
  7. Advanced data mining and machine learning pipelines — build and critically evaluate, integrating statistical rigor with computational methods for high-dimensional datasets.
  8. Peer and client review sessions — lead independently, presenting nuanced statistical results and nonstatistical implications to mixed audiences including executives, scientists, and policymakers.
  9. Interdisciplinary research teams — serve as the statistical authority, advising collaborators on analytic strategy and interpreting quantitative evidence within broader scientific context.
  10. Systems of data collection and measurement — analyze for bias, efficiency, and fitness-for-purpose, recommending design improvements to organizational data infrastructure.
Advanced
Lead / Principal / Executive
  1. Organizational statistical strategy — define and champion methodological standards, governance frameworks, and quality benchmarks across an enterprise or major research institution.
  2. Novel statistical methodologies — pioneer and publish, advancing discipline knowledge and establishing best practices adopted by professional communities or regulatory bodies.
  3. Statistical workforce development — mentor, train, and evaluate teams of statisticians at multiple career levels, designing learning pathways aligned to organizational capability needs.
  4. Cross-functional analytical agendas — set in collaboration with C-suite or agency leadership, translating strategic priorities into rigorous quantitative research programs.
  5. Validity and integrity of large-scale data systems — oversee at the institutional level, establishing evaluation criteria and directing audit processes for enterprise analytical platforms.
  6. High-stakes statistical reports and expert testimony — author and present before regulatory agencies, legislative bodies, or executive boards, with full accountability for conclusions.
  7. Research design frameworks — establish for multi-site or longitudinal studies, coordinating statistical coherence across distributed teams and data sources.
  8. Organizational adoption of advanced analytical tools — lead, selecting and integrating business intelligence, data mining, and scientific software ecosystems to support strategic decision-making.
  9. Ethical and policy dimensions of statistical practice — guide at the institutional level, ensuring data privacy, equity in measurement, and responsible use of inference across all projects.
  10. External partnerships and funding — cultivate with government agencies, industry sponsors, and academic consortia, positioning the organization as a recognized center of statistical excellence.

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.
Subscriber feature

Authoritative source data identified for 998 occupations

How a worker at each mastery level uses, directs, and evaluates AI tools in this occupation. Each statement cites its evidence inline; click a citation chip to verify the source.

Emerging
  1. AI-generated summary statistics — accepts descriptive outputs from AI tools for exploratory data analysis tasks, cross-checking results against manually computed reference values before reporting Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab..
  2. Basic code scaffolding — uses AI assistants to generate starter R or Python scripts for standard statistical procedures, reviewing each line for correctness before execution Jadhav & Danve, 2026Skill Automation Feasibility Index — Jadhav & Danve, 2026 (arXiv:2604.06906). Opens in new tab..
Developing
  1. Data preparation delegation — directs AI tools to handle routine data-cleaning steps such as detecting missing values, flagging outliers, and applying weighting schemes, then audits every transformation against the raw data Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab..
  2. Visualization drafting — instructs an AI assistant to produce initial chart and table layouts for statistical reports, then refines axes, scales, and annotations to meet analytical standards Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab..
  3. Method selection screening — queries an AI assistant for candidate statistical methods given a research question, then applies domain expertise and validity criteria to confirm or override the recommendation 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..
Proficient
  1. Full analytical pipeline coordination — directs AI tools across the complete workflow from data ingestion through model fitting and residual diagnostics, retaining authorship of all inferential decisions Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab. WEF Skills TaxonomyWEF Skills Taxonomy 2021 — Building a Common Language for Skills at Work. Opens in new tab..
  2. Assumption validation oversight — tasks an AI assistant with running distributional and independence checks, then independently interprets outputs to confirm that underlying statistical assumptions hold before proceeding Jadhav & Danve, 2026Skill Automation Feasibility Index — Jadhav & Danve, 2026 (arXiv:2604.06906). Opens in new tab..
  3. Reporting automation — delegates structured narrative generation and figure embedding to an AI tool for routine statistical reports, editing every interpretive claim for accuracy and appropriate uncertainty quantification Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab..
  4. Procedure evaluation — uses AI-assisted literature synthesis to audit the validity, applicability, and efficiency of statistical procedures applied by external teams, applying critical judgment to resolve conflicts between AI-surfaced sources and primary methodology references 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..
Advanced
  1. High-autonomy AI orchestration with risk management — deploys AI agents across multi-stage statistical projects operating at mean autonomy levels that demand active human governance checkpoints, setting explicit acceptance criteria and rollback conditions at each stage 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..
  2. Methodology governance — establishes organizational standards for which statistical tasks AI tools are authorized to execute independently versus which require statistician sign-off, grounded in automation-feasibility evidence for mathematics-intensive skills positioned in the high-displacement-risk quadrant 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..
  3. Efficiency-gain accountability — quantifies and communicates the time savings realized through AI-assisted statistical workflows to stakeholders, while documenting residual error rates and model limitations to ensure decision-makers understand the basis of reported findings Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab..
  4. Cross-functional AI capability advising — guides data-science and research teams on appropriate boundaries of AI delegation in statistical work, translating augmentation-share and autonomy metrics into practical governance policies that protect inferential integrity Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab. WEF Skills TaxonomyWEF Skills Taxonomy 2021 — Building a Common Language for Skills at Work. Opens in new tab..
Evidence pack
AEI usage
Task observations: 1329
Augment share: 95%
Time saved: 80.3%
AI autonomy: 3.20
SAFI positioning
Top skill: Mathematics
Score: 73.2 / 100
Quadrant: Q1_high_displacement_risk
precision: exact
WEF cluster
Artificial Intelligence
artificial_intelligence
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.

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.
Subscriber feature

Ten durable-skill domains mapped to four proficiency/role levels for each occupation. Each statement is aligned to the Pathsmith taxonomy, derived from trusted grounding data and mapped to occupation-specific O*NET tasks and skills.

1Communication10 statements
Emerging
  1. Statistical report drafting — translates basic analytical outputs into written summaries using standard templates for internal team review 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.
  2. Data visualization basics — constructs simple charts and graphs to represent statistical findings for non-technical audiences O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
Developing
  1. Findings presentation — delivers statistical results using charts, bullets, and graphs in departmental meetings, adjusting vocabulary for mixed technical and non-technical audiences 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.
  2. Methodology documentation — writes clear descriptions of sampling techniques and analytical procedures for replication by peers O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
  3. Active listening in client intake — elicits research questions and user needs through structured dialogue to ensure appropriate statistical method selection 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.
Applying
  1. Client-facing results communication — presents complex multivariate findings to stakeholders such as clients and executives using layered visualizations and narrative summaries that foreground actionable insights 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.
  2. Cross-functional technical writing — authors statistical methods sections, appendices, and executive summaries within research reports that serve both regulatory and scientific audiences O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
  3. Conference presentation — delivers statistical analyses at professional conferences, responding to peer questions with precise methodological justification 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.
Exceeding
  1. Statistical communication strategy — architects organization-wide standards for reporting statistical results, including style guides for data visualization and written interpretation used by junior analysts 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.
  2. Translational expertise — distills highly complex statistical models and uncertainty estimates into accessible policy briefs or board-level summaries without sacrificing analytical integrity 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.
2Leadership9 statements
Emerging
  1. Project contribution ownership — takes responsibility for assigned data preparation tasks, flagging inaccuracies and communicating progress to project leads without prompting Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Peer support initiation — shares knowledge of basic statistical software functions or coding syntax with teammates during collaborative analysis sessions Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Developing
  1. Analytical workstream coordination — organizes subtasks within a statistical project, assigning data-cleaning and validation steps to team members and tracking completion Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Junior analyst guidance — demonstrates correct application of sampling techniques or weighting procedures to entry-level staff during active project work 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.
Applying
  1. Research project leadership — leads end-to-end statistical studies, defining scope, selecting methods, assigning roles, and ensuring delivery of valid and timely results to clients or stakeholders 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.
  2. Methodological decision authority — makes final determinations on appropriateness of statistical procedures based on research question and data characteristics, assuming accountability for analytical validity O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
  3. Interdisciplinary team direction — guides subject-matter experts and data engineers toward statistically sound study designs by setting clear analytical requirements and review checkpoints Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Exceeding
  1. Statistical center of excellence leadership — establishes and leads a team of statisticians, setting professional development goals, instituting code review practices, and driving adoption of best-in-class methods Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Organizational influence — champions evidence-based decision-making culture across business units by modeling rigorous statistical reasoning and holding others accountable to data quality standards 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.
3Metacognition9 statements
Emerging
  1. Self-assessment of method selection — reflects on whether a chosen statistical test matches the distributional assumptions of the data before finalizing analysis 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.
  2. Error recognition — identifies gaps in personal understanding of a procedure and seeks reference materials or mentor review before proceeding Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Developing
  1. Analytical process monitoring — tracks own reasoning at each stage of a statistical workflow, noting where assumptions were made and documenting rationale for method choices 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.
  2. Skill gap mapping — evaluates personal proficiency across statistical domains such as Bayesian inference or time-series modeling and creates a targeted learning plan Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Applying
  1. Pre-analysis planning — constructs detailed analytic plans before accessing data, explicitly identifying potential confounders, limitations, and contingency methods to guard against post-hoc rationalization 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.
  2. Post-project reflection — conducts structured self-review after project delivery, identifying where alternative methods could have improved validity or efficiency and documenting lessons for future work Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  3. Assumption auditing — systematically evaluates own model assumptions mid-analysis, adjusting methodology when diagnostic checks reveal violations 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.
Exceeding
  1. Metacognitive mentorship — teaches junior statisticians to monitor their own analytical reasoning, introducing structured peer-review and self-critique protocols into team workflows Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Epistemological rigor — interrogates the boundaries of one's own statistical knowledge domain when approaching novel data types or research designs, actively seeking expert collaboration before drawing conclusions 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.
4Critical Thinking10 statements
Emerging
  1. Data validity questioning — identifies obvious anomalies such as out-of-range values or missing data patterns during initial data inspection and flags them for review 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.
  2. Assumption identification — recognizes stated assumptions underlying a given statistical model and lists potential violations for discussion with a supervisor 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.
Developing
  1. Statistical method evaluation — assesses whether a proposed analytical procedure is valid and efficient given the research question, sample size, and data distribution 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.
  2. Source triangulation — compares results across multiple data sources to detect inconsistencies that could indicate measurement error or sampling bias 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.
  3. Confounding analysis — identifies variables that could distort the relationship between variables of interest and recommends control strategies O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
Applying
  1. Evidence-based methodology selection — evaluates competing statistical approaches against criteria of validity, applicability, and accuracy, selecting and defending the optimal method with documented reasoning 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.
  2. Trend and relationship analysis — distinguishes statistically significant patterns from noise within large datasets, assessing practical significance alongside p-values and confidence intervals O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
  3. Experimental design critique — reviews proposed study designs for logical flaws, selection bias, or underpowered samples before data collection begins 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.
Exceeding
  1. Statistical epistemology leadership — leads peer review of analytical methods across projects, applying advanced critical appraisal to identify subtle methodological threats to internal and external validity 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.
  2. Meta-analytic judgment — synthesizes findings across multiple studies or data sources, critically evaluating heterogeneity, publication bias, and generalizability to produce authoritative conclusions 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.
5Collaboration9 statements
Emerging
  1. Cross-team data handoff — receives raw datasets from partner teams, confirms file formats and variable definitions, and acknowledges discrepancies before analysis begins 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.
  2. Meeting participation — contributes statistical perspective during project planning meetings, listening actively to domain experts to understand research context 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.
Developing
  1. Subject-matter expert partnership — collaborates with domain scientists or business analysts to align statistical design with disciplinary constraints and practical requirements 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.
  2. Shared code development — contributes to collaborative codebases for data processing and analysis, adhering to team conventions and reviewing peers' scripts Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Applying
  1. Interdisciplinary research collaboration — serves as the statistical lead within multidisciplinary project teams, integrating contributions from data engineers, domain experts, and clients into a coherent analytical plan 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.
  2. Conflict navigation in analysis decisions — facilitates resolution of disagreements between analysts and stakeholders about method choice by grounding discussion in empirical evidence and shared research objectives Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  3. Peer review participation — provides substantive methodological critique during internal review cycles, balancing candor with respect for colleagues' analytical decisions Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Exceeding
  1. Collaborative framework design — co-creates organization-wide data governance and analytical collaboration protocols with IT, legal, and research teams, ensuring statistical rigor is embedded across functions Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. External research consortium leadership — represents the organization in multi-institution collaborative studies, coordinating harmonized data collection and analysis standards across partner sites 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.
6Character9 statements
Emerging
  1. Data integrity commitment — reports data inaccuracies discovered during preparation rather than adjusting values without documentation, even when corrections create delays 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.
  2. Transparent uncertainty reporting — acknowledges limitations of preliminary findings when presenting early-stage results to supervisors Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Developing
  1. Ethical data handling — applies appropriate anonymization and access controls to sensitive datasets in accordance with research ethics protocols and organizational policy 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.
  2. Methodological honesty — discloses when a statistical method has known limitations relevant to the current application, recommending supplementary analyses rather than suppressing caveats 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.
Applying
  1. Research integrity enforcement — identifies and reports instances of p-hacking, selective reporting, or outcome switching in collaborative projects, advocating for pre-registration and transparent reporting standards 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.
  2. Accountable deliverable ownership — accepts responsibility for errors in published analyses, initiates corrections, and implements process changes to prevent recurrence Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  3. Professional conduct under pressure — maintains analytical objectivity when stakeholders request favorable interpretations of ambiguous results, delivering accurate findings regardless of preference 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.
Exceeding
  1. Institutional ethics leadership — develops and advocates for organizational codes of statistical ethics, including policies on data fabrication, selective reporting, and informed consent for data use Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Role modeling professional accountability — publicly acknowledges and corrects published errors in one's own work, setting a standard of intellectual honesty that strengthens team and organizational credibility Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
7Creativity9 statements
Emerging
  1. Visualization experimentation — explores alternative chart types or color encodings to represent a dataset more intuitively than default outputs provide 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.
  2. Proxy variable ideation — proposes alternative measurable variables when ideal data are unavailable to operationalize a research construct Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Developing
  1. Analytical method adaptation — modifies standard statistical procedures to better fit an unconventional data structure or novel research question 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.
  2. Sampling innovation — designs creative stratification schemes that improve representativeness within cost and logistical constraints of a study O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.
Applying
  1. Novel study design development — invents experimental or quasi-experimental designs suited to complex causal questions where randomization is infeasible, combining multiple methodological traditions 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.
  2. Integrative modeling — synthesizes techniques from disparate statistical subfields, such as combining machine learning classifiers with traditional inferential tests, to address problems no single method resolves 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.
  3. Data storytelling innovation — crafts interactive or animated data visualizations that transform static statistical reports into compelling, exploratory narratives for diverse stakeholders 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.
Exceeding
  1. Methodological invention — develops novel statistical estimators, sampling algorithms, or model architectures in response to data challenges that existing methods cannot adequately address, contributing to the field through publication or open-source release 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.
  2. Creative problem reframing — reconceptualizes a stakeholder's research question to reveal a more tractable or insightful statistical formulation, unlocking analytical approaches that were previously overlooked Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
8Growth Mindset9 statements
Emerging
  1. Feedback integration — incorporates supervisor critique of analytical output by revising code or interpretation rather than defending the initial approach Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. New method exploration — voluntarily studies an unfamiliar statistical technique when a project requires it, using documentation and tutorials to build competence 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.
Developing
  1. Failure analysis — when a model performs poorly on validation data, diagnoses root causes systematically and applies corrective strategies rather than abandoning the approach 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.
  2. Continuing education pursuit — identifies and completes formal training in emerging areas such as Bayesian computation or causal inference to expand methodological repertoire 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.
Applying
  1. Iterative model refinement — treats initial model diagnostics as learning inputs, cycling through assumption testing and re-specification until results meet validity standards 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.
  2. Peer learning culture contribution — shares lessons from analytical failures and project retrospectives with team members, framing setbacks as collective learning opportunities Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  3. Complexity embrace — voluntarily takes on research problems that require mastery of unfamiliar data types or domains, viewing the learning curve as intrinsic to professional development Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Exceeding
  1. Field-wide learning leadership — curates and leads internal learning communities, journal clubs, or workshops where statisticians engage with cutting-edge methodological literature to sustain collective growth Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Adaptive methodology adoption — rapidly acquires and deploys newly published statistical methods when they offer meaningful advances over current practice, integrating them into live projects and team standards 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.
9Mindfulness9 statements
Emerging
  1. Focused data review — allocates uninterrupted time blocks for data validation tasks, minimizing context-switching to reduce transcription and logic errors 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.
  2. Stress awareness during deadlines — recognizes personal cognitive load signals during high-pressure reporting cycles and applies brief reset strategies before resuming analysis Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Developing
  1. Intentional assumption checking — pauses at defined checkpoints in the analytical workflow to deliberately re-examine whether initial data assumptions still hold as the analysis evolves 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.
  2. Emotion regulation in stakeholder feedback — maintains analytical composure when clients challenge statistical conclusions, responding with evidence rather than defensiveness Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Applying
  1. Deliberate pace under complexity — slows analytical decision-making when working with high-dimensional or ambiguous data, resisting premature closure in favor of thorough investigation 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.
  2. Present-moment quality control — applies mindful attention during final report review, catching interpretive overreach or visualization errors that automated checks miss 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.
  3. Intentional communication pacing — gauges audience comprehension in real time during statistical presentations and adjusts depth and pace accordingly 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.
Exceeding
  1. Mindful analytical culture stewardship — institutionalizes deliberate review practices such as pre-mortem analyses and structured pause points into team project workflows, reducing systematic errors across the group Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Sustained attentional leadership — models and teaches techniques for maintaining focused, unbiased attention during long-horizon data projects, improving team output quality under sustained cognitive demand Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
10Fortitude9 statements
Emerging
  1. Persistence through data problems — continues working through messy or incomplete datasets, iterating on cleaning strategies rather than requesting a restart 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.
  2. Uncertainty tolerance — proceeds with analysis under ambiguous conditions by documenting assumptions explicitly and flagging sensitivity to those assumptions Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Developing
  1. Resilience through model failure — rebuilds analytical approach after initial model specifications fail diagnostic tests, maintaining confidence in the iterative process 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.
  2. Sustained effort on complex problems — maintains engagement across multi-week statistical projects with evolving requirements, recalibrating priorities without losing analytical momentum Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
Applying
  1. Adversarial finding delivery — presents statistically sound but organizationally unwelcome findings to senior stakeholders without softening conclusions, supported by transparent methodology 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.
  2. Long-horizon research endurance — sustains rigorous analytical standards across extended longitudinal studies or multi-phase research programs spanning months or years 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.
  3. Recovery from replication failure — when independent replication contradicts prior results, leads methodical investigation into discrepancies and revises conclusions based on accumulated evidence 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.
Exceeding
  1. Organizational courage in data disputes — confronts institutional pressure to alter statistical conclusions by escalating concerns through appropriate channels and documenting objections formally Pathsmith Durable SkillsPathsmith Durable Skills Framework — America Succeeds + CompTIA. Opens in new tab.
  2. Crisis analysis leadership — leads statistical response teams during data emergencies such as large-scale data breaches, system failures, or rapidly evolving public health events, maintaining rigor and composure under acute pressure 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.
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
Analytical Statistician · Applied Scientist · Applied Statistician · Biometrician · Clinical Analyst · Data Analyst · Data Analyst Specialist · Data Analytics Specialist · Data Coordinator · Data Engineer · Data Manager · Data Modeler
RAPIDS apprenticeships
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O*NET skills
MathematicsReading ComprehensionCritical ThinkingSpeakingActive ListeningComplex Problem SolvingWritingActive LearningScienceJudgment and Decision MakingLearning StrategiesMonitoringProgrammingSystems AnalysisSystems EvaluationTime Management
Knowledge domains
MathematicsComputers and ElectronicsEnglish Language
Abilities
Mathematical ReasoningNumber FacilityWritten ComprehensionOral ComprehensionInductive ReasoningOral ExpressionNear VisionWritten ExpressionDeductive ReasoningInformation Ordering
Work styles
Attention to DetailIntellectual CuriosityDependabilityAchievement OrientationIntegrityCautiousness
Technology
Data base user interface and query softwareData mining softwareData base management system softwareBusiness intelligence and data analysis softwareAnalytical or scientific softwareObject or component oriented development softwareDevelopment environment softwareEnterprise application integration softwareOperating system softwareSpreadsheet software
Tasks · seed anchors for statements
  1. Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
  2. Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
  3. Report results of statistical analyses, including information in the form of graphs, charts, and tables.
  4. Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
  5. Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
  6. Develop and test experimental designs, sampling techniques, and analytical methods.
  7. Identify relationships and trends in data, as well as any factors that could affect the results of research.
  8. Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.
CIP education codes
13.060313.060413.060813.069926.110126.110226.131127.010127.030127.030427.050127.050227.050327.059927.060130.490130.700130.709930.710130.710230.719942.270845.010245.010345.060352.1302

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.