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Quantitative Model Validation Analyst Jobs in Raleigh, NC

Develop AI models and datasets to inform business decisions, correlate data and drive decision ... quantitative field (Master's degree preferred). * A minimum of 5 years of experience in data ...

Develop AI models and datasets to inform business decisions, correlate data and drive decision ... quantitative field (Master's degree preferred). * A minimum of 5 years of experience in data ...

Develop AI models and datasets to inform business decisions, correlate data and drive decision ... quantitative field (Master's degree preferred). * A minimum of 5 years of experience in data ...

Senior Modeling Engineer

Raleigh, NC · On-site

$166K - $181K/yr

Develop data extraction logic and perform model validation. Configure and integrate software ... point generation and analysis within the SCADA application. Contact: Apply online at www ...

Sr. Compensation Analyst

Raleigh, NC · On-site

$73K - $95K/yr

Responsible for data implementation, auditing and data validation, and system analytics. * Provide ... Strong business acumen, analytical, quantitative, and problem-solving skills, including keen ...

Sr. Compensation Analyst

Raleigh, NC · Hybrid

$73K - $95K/yr

Responsible for data implementation, auditing and data validation, and system analytics. * Provide ... Strong business acumen, analytical, quantitative, and problem-solving skills, including keen ...

... quantitative analysis, and effective project execution. This role enables datadriven category ... financial modeling of global category projects, evaluating local initiatives, and ensuring ...

... quantitative analysis, and effective project execution. This role enables data‑driven category ... financial modeling of global category projects, evaluating local initiatives, and ensuring ...

... quantitative analysis, and effective project execution. This role enables data‑driven category ... financial modeling of global category projects, evaluating local initiatives, and ensuring ...

... relationships - Models integrity and company values - Seeks out growth and breakthrough ... analyzing resumes, or assessing responses. These tools assist our recruitment team but do not ...

Business Analyst

Raleigh, NC · On-site +1

$68K - $82K/yr

Gather, validate, and document business requirements from stakeholders; translate them into clear ... Analyze quantitative and qualitative data to identify trends, root causes, opportunities, and risks.

... relationships - Models integrity and company values - Seeks out growth and breakthrough ... analyzing resumes, or assessing responses. These tools assist our recruitment team but do not ...

... quantitative analysis, and effective project execution. This role enables data-driven category ... financial modeling of global category projects, evaluating local initiatives, and ensuring ...

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Showing results 1-20

Quantitative Model Validation Analyst information

See Raleigh, NC salary details

$54.9K

$130.1K

$233.3K

How much do quantitative model validation analyst jobs pay per year?

As of Jun 10, 2026, the average yearly pay for quantitative model validation analyst in Raleigh, NC is $130,132.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,400.00 and $141,400.00 per year, depending on experience, location, and employer.

What are Quantitative Model Validation Analysts?

Quantitative Model Validation Analysts are professionals who assess and validate financial models used by banks and financial institutions. They ensure that these models are accurate, reliable, and comply with regulatory standards. Their work involves testing model assumptions, reviewing model methodologies, and analyzing model outputs to identify potential risks or weaknesses. By providing an independent review, they help organizations maintain the integrity and performance of their risk management and financial forecasting tools.

What are some typical challenges faced by Quantitative Model Validation Analysts when assessing complex financial models?

Quantitative Model Validation Analysts often encounter challenges such as interpreting intricate model methodologies, ensuring data integrity, and effectively communicating technical findings to stakeholders who may not have a quantitative background. Additionally, staying current with evolving regulatory requirements and industry standards can be demanding. Collaborating closely with model developers, risk managers, and auditors is crucial to address model limitations and propose actionable improvements, making strong communication and analytical skills essential for success in this role.

What is the difference between Quantitative Model Validation Analyst vs Quantitative Risk Analyst?

AspectQuantitative Model Validation AnalystQuantitative Risk Analyst
CredentialsTypically requires a degree in finance, mathematics, or statistics; certifications like CFA or FRM are commonSimilar credentials; often holds CFA, FRM, or related certifications
Work EnvironmentFocuses on validating models used in risk management, trading, or credit scoring within financial institutionsAnalyzes and manages financial risk, including market, credit, and operational risks in banking or investment firms
Industry UsageCommonly employed in banking, asset management, and insurance sectorsWidely used in banking, hedge funds, and financial services

The main difference is that Quantitative Model Validation Analysts focus on testing and validating models to ensure accuracy and compliance, while Quantitative Risk Analysts assess and manage overall financial risks. Both roles require strong quantitative skills and often overlap in credentials and work environments, but their core responsibilities differ in scope and focus.

What are the key skills and qualifications needed to thrive as a Quantitative Model Validation Analyst, and why are they important?

To thrive as a Quantitative Model Validation Analyst, you need a strong background in quantitative finance, statistics, and programming, typically supported by a degree in mathematics, finance, or a related field. Familiarity with statistical software such as Python, R, MATLAB, and model risk management frameworks is essential, and certifications like FRM or CFA are advantageous. Analytical thinking, attention to detail, and effective communication skills set top performers apart by enabling them to explain complex model risks and recommendations clearly. These skills and qualities are vital for ensuring the accuracy, reliability, and regulatory compliance of financial models within an organization.
What are popular job titles related to Quantitative Model Validation Analyst jobs in Raleigh, NC? For Quantitative Model Validation Analyst jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Quantitative Model Validation Analyst jobs in Raleigh, NC look for? The top searched job categories for Quantitative Model Validation Analyst jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Quantitative Model Validation Analyst jobs? Cities near Raleigh, NC with the most Quantitative Model Validation Analyst job openings:
Infographic showing various Quantitative Model Validation Analyst job openings in Raleigh, NC as of June 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $130,132 per year, or $62.6 per hour.

$110/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 2 days ago


Job description

Reports To: Chief of Staff

 

This role requires a full-time onsite presence in Durham, NC

 

Target Base Range: $110 - 120k (Final compensation commensurate with experience and qualifications) 

 

Please note: We are only able to consider candidates who are U.S. citizens or lawful permanent residents (green card holders) and who do not require current or future visa sponsorship of any sort.

 

About the Role

We are seeking a highly skilled Senior Data Analyst with a strong foundation in data science, statistical modeling, and advanced analytics and AI platforms to drive data-informed decision-making across the organization. This role sits at the intersection of AI, analytics, data science, and business strategy-transforming complex data into actionable insights, predictive solutions, and measurable outcomes.

The ideal candidate is comfortable working with large, complex datasets, building advanced analytical models, and communicating findings clearly to both technical and non-technical stakeholders.

Key Responsibilities

Data Analytics & Insights

  • Analyze large, complex, and multi-source datasets to uncover trends, patterns, and actionable insights.
  • Translate analytical findings into clear recommendations that influence product strategy, operations, and executive decision-making.
  • Develop data-driven forecasts, simulations, and scenario analyses to support strategic planning.
  • Apply statistical techniques (e.g., regression, hypothesis testing, time-series analysis, clustering) to solve complex business problems.

Data Engineering & Tooling (Analytics-Focused)

  • Develop AI models and datasets to inform business decisions, correlate data and drive decision-making.
  • Write efficient, well-documented SQL and/or Python/R code for data extraction, transformation, and analysis.
  • Partner with data engineering teams to ensure high-quality, well-structured, and reliable datasets.
  • Maintain internal utilization models and support continual enhancement and development of utilization models.

Leadership & Collaboration

  • Act as a thought leader and mentor for team members and business partners.
  • Collaborate closely with stakeholders across product, finance, operations, marketing, and quality.
  • Help define best practices for analytics, experimentation, and data science across the organization.

Required Qualifications

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field (Master's degree preferred).
  • A minimum of 5 years of experience in data analytics, data science, or a related analytical role.
  • Strong knowledge of statistical analysis, modeling techniques, and data science methodologies.
  • Experience working with large datasets and modern data platforms (e.g., cloud data warehouses, distributed systems).
  • Proven ability to translate data insights into business impact.
  • Excellent communication and stakeholder management skills.

Preferred / Nice-to-Have Qualifications

  • Experience deploying or operationalizing machine learning models in a production environment.
  • Familiarity with A/B testing frameworks and experimental design.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and modern analytics stacks.
  • Knowledge of data governance, data quality, and privacy best practices.
  • Prior experience in EV Charging, consumer behavior, technical quality analytics.

What Success Looks Like in This Role

  • You own the pursuit of the truth in everything you do.
  • Analytical insights consistently influence strategic and operational decisions with clarity and conviction.
  • Predictive models and advanced analyses improve forecasting accuracy and business outcomes.
  • Stakeholders trust and rely on analytics outputs for critical decisions.
  • Analytics processes are scalable, efficient, and reproducible.

IONNA is committed to fair and equitable compensation practices through a competitive base salary, as well as offering bonus programs, comprehensive benefits such as medical, dental, vision, life, 401(K), and paid holidays. Actual base salaries are based on several factors unique to each candidate, including but not limited to skill set, experience, certifications, and specific work location.

We are committed to an inclusive and diverse team. IONNA is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.