Quantitative Enterprise Risk Management Analyst

CVS Health•Work At Home-Texas, TX

1d•$43,888 - $85,068

About The Position

This risk management position supports CVS Health’s Enterprise Risk Management (ERM) program across quantitative risk analysis, regulatory deliverables, and broader ERM activities. Under the direction of ERM leadership, the analyst helps maintain and enhance quantitative models, support regulatory and risk-management processes, and collaborate with subject matter experts across the enterprise. The role calls for a detail-oriented, analytically minded, intellectually curious self-starter who develops technical expertise, understands the business context behind analyses, and takes increasing ownership of complex models and recurring ERM processes. The analyst combines data and technical skills with clear communication, sound judgment, and a collaborative approach. The position supports the enterprise economic capital model and other risk-quantification tools, including investigation of issues, evaluation and implementation of changes, testing and reconciliation of results, and communication of updates’ rationale and impact. It involves working with complex datasets, quantitative and statistical analysis, stress scenarios, and repeatable reporting using tools such as SQL and Excel, and where applicable VBA, R, or Python. The analyst also maintains clear, accurate, auditable documentation and contributes to improvements in data quality, model controls, documentation, and process efficiency. This is a full-time position with 40 anticipated weekly hours. The typical pay range is $43,888 to $85,068. The role is eligible for a CVS Health bonus, commission, or short-term incentive program in addition to base pay. The full-time benefits package includes medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. The anticipated application window closes on November 27, 2026.

Requirements

Foundational experience with quantitative analysis, financial or statistical modeling, or complex analytical coursework or projects.
Proficiency in Microsoft Excel, with working knowledge of SQL and VBA.
Demonstrated attention to detail and commitment to accuracy, completeness, data integrity, and clear, well-organized documentation.
Ability and willingness to learn complex quantitative models, understand how their components connect, and build subject-matter expertise to maintain and enhance them over time.
Self-starter mindset with the ability to ask thoughtful questions, identify issues, recommend practical improvements, incorporate feedback, and take increasing ownership of assignments.
Bachelor’s degree, or equivalent experience, in a quantitative, analytical, finance, business, or related field.

Nice To Haves

Exposure to financial statements, statistical concepts, risk management, or scenario analysis.
Experience using PowerQuery.
Experience working with large or complex datasets, including data-quality review, reconciliation, and documentation.
Experience using R or Python for data preparation, statistical analysis, modeling, visualization, or automation.
Foundational knowledge of the health care industry, accounting, finance, or regulatory reporting.
Experience with GRC, project-management, model-governance, or workflow tools.
Intellectual curiosity and adaptability, with an interest in continuously learning about enterprise risks, regulatory requirements, and business processes.

Responsibilities

Develop a deep understanding of assigned quantitative risk models, including data flows, calculations, assumptions, dependencies, controls, outputs, and business context, and take increasing ownership of their maintenance and enhancement.
Support the enterprise economic capital model and other risk-quantification tools by investigating issues, evaluating and implementing changes, testing and reconciling results, and explaining the rationale and impact of updates.
Partner with subject matter experts and cross-functional teams to collect and interpret data, understand source-system and business definitions, develop or validate assumptions, and translate business information into quantitative analysis.
Prepare and analyze complex datasets through profiling, cleansing, standardization, validation, reconciliation, transformation, aggregation, trend analysis, and data-quality control checks.
Use SQL, Excel, and, where applicable, VBA, R, or Python to extract and transform data, perform quantitative and statistical analysis, support modeling, automate processes, and produce repeatable reporting.
Maintain clear, accurate, and auditable documentation of data sources, business rules, model methodologies, assumptions, limitations, changes, testing, results, and governance activities within designated systems and tracking tools.
Support stress-scenario development and execution and enterprise risk quantification.
Build productive relationships with internal and external stakeholders, communicate technical concepts clearly to technical and non-technical audiences, provide timely status updates, and raise issues promptly.
Take ownership of assignments, ask thoughtful questions, incorporate feedback, and proactively identify opportunities to improve data quality, model controls, documentation, and process efficiency while supporting broader ERM initiatives.