{"schemaVersion":"1.0","exportedAt":"2026-05-15T12:38:27.345Z","occupation":{"soc":"13-2099.01","title":"Financial Quantitative Analysts","group":"Business & Financial Operations","sector":"55","jobZone":5,"jobZoneInferred":false},"framework":{"version":"v.26.05","description":"","contextCovered":"This framework covers quantitative finance practice across derivative valuation, portfolio optimization, risk management, pricing model development, and regulatory compliance in institutional financial environments requiring advanced mathematical and computational expertise.","levels":{"emerging":{"label":"Emerging","statements":["Standard statistical techniques — apply under structured guidance to introductory finance problems such as return distribution analysis in a supervised research environment.","Existing pricing model libraries — execute and test using analytical or scientific software under senior analyst direction on assigned asset classes.","Financial data sets — query and extract using database user interface and query software to support team research workflows.","Quantitative analysis results — interpret and summarize in written form under reviewer oversight for internal research reports.","Mathematical reasoning and number facility — demonstrate by performing routine derivative valuation calculations within established model frameworks.","Data collection methods — assist in defining under supervision by documenting data sources and flagging quality issues for senior review.","Financial research literature — read and synthesize relevant peer-reviewed material to support team model development initiatives.","Analytical support tasks — provide to researchers and traders by running pre-built valuation queries and returning structured outputs.","Statistical software tools and development environments — operate at a proficient level to execute assigned quantitative scripts and pipelines.","Financial analysis findings — present orally in team meetings under the guidance of a senior quantitative analyst in a structured review setting."]},"developing":{"label":"Developing","statements":["Applied mathematical and econometric techniques — deploy with reduced oversight to address practical risk management and securities trading problems in live market environments.","Portfolio optimization models — develop and calibrate using advanced quantitative methods to support portfolio construction decisions across assigned strategies.","Analytical results from financial models — interpret and translate into actionable insights for trading desk stakeholders with minimal senior intervention.","Model libraries — maintain and modify routinely by updating parameters, correcting errors, and validating outputs within an established model governance framework.","Data mining and analytical software — leverage independently to explore large financial data sets and identify statistically significant patterns for team use.","Written summary reports — produce that clearly communicate quantitative research findings, methodology, and limitations to both technical and non-technical audiences.","Model specification recommendations — formulate and propose for peer review by evaluating alternative functional forms and data inputs for pricing or attribution models.","Performance measurement and attribution frameworks — build and apply to evaluate portfolio returns against benchmarks in an asset management environment.","Econometric and statistical model assumptions — critically evaluate using deductive and inductive reasoning to identify potential model risk before deployment.","Analytical support — provide responsively to traders and researchers on valuation and data issues, applying sound judgment to resolve moderate-complexity queries independently."]},"proficient":{"label":"Proficient","statements":["Advanced mathematical and statistical methodologies — apply autonomously across the full scope of derivative valuation, risk management, and financial market regulation challenges in complex, fast-moving environments.","Novel analytical tools for portfolio construction and optimization — research, design, and validate independently, incorporating cutting-edge quantitative and econometric techniques.","Non-routine financial analysis results — interpret with high confidence, identifying model limitations and market anomalies, and communicating conclusions to senior leadership.","Core quantitative model libraries — architect and maintain across multiple asset classes, ensuring robustness, version control, and compliance with regulatory standards.","Data collection methodologies and model specifications — define authoritatively by assessing trade-offs among data quality, computational cost, and statistical validity.","Comprehensive financial research reports — produce that integrate multi-factor quantitative findings into strategic recommendations for investment committees or regulators.","Object-oriented and development environment software — utilize at an expert level to build scalable, production-grade analytical systems supporting trading and risk functions.","Complex valuation and risk quantification problems — resolve for traders and researchers by synthesizing mathematical reasoning, market knowledge, and system-level thinking.","Enterprise risk management and ERP systems — integrate quantitative model outputs into, ensuring accurate profit-and-loss measurement and regulatory capital reporting.","Analytical judgment on ambiguous financial problems — exercise by applying systems analysis and evaluation skills to deliver sound decisions under data uncertainty."]},"advanced":{"label":"Advanced","statements":["Firmwide quantitative research strategy — set and drive by defining multi-year model development roadmaps aligned to business objectives across trading, risk, and compliance functions.","Organizational model governance frameworks — establish and oversee, ensuring all financial analytic models meet rigorous validation, audit, and regulatory standards at an institutional scale.","Senior quantitative talent — develop and mentor by designing learning pathways, providing technical sponsorship, and building a high-performance research culture.","Cross-functional analytical capabilities — lead by directing collaborative initiatives between quantitative analysts, technologists, traders, and regulators to address systemic financial risk.","Innovative pricing and risk model architectures — pioneer by championing adoption of frontier statistical, machine-learning, and econometric methodologies across the enterprise.","Executive and board-level stakeholders — persuade and advise by translating complex quantitative insights into strategic financial decisions with clarity and authoritative judgment.","Industry-wide standards for quantitative methods — influence by contributing to regulatory consultations, academic publications, and professional bodies shaping financial market practice.","Enterprise data infrastructure strategy — define in partnership with technology leadership to ensure scalable, high-integrity data pipelines supporting all quantitative functions.","Organizational risk appetite and model risk policy — shape by synthesizing systems-level evaluation of model performance, market conditions, and regulatory expectations.","Firmwide analytical tool ecosystems — oversee continuous evolution of, coordinating procurement, build-versus-buy decisions, and integration of advanced financial analysis software platforms."]}}},"sources":{"onet":"v30.2 (CC BY 4.0)","crosswalk":"https://skillscrosswalk.com","generator":"LER.me"},"attribution":"© EBSCOed"}