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Quantitative Model Validation Analyst Jobs in Edmond, OK

Gainwell Technologies

Business Analyst

Oklahoma City, OK · On-site

$51K - $74K/yr

... and process models * Create, execute or analyze basic test scenarios to verify that client ... Advanced knowledge in Microsoft Excel and other software for conducting quantitative analysis

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All JobsQuantitative Model Validation Analyst JobsQuantitative Model Validation Analyst Jobs in Edmond, OK

Quantitative Model Validation Analyst information

See Edmond, OK salary details

$50.4K

$119.4K

$214K

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

As of Aug 27, 2026, the average yearly pay for quantitative model validation analyst in Edmond, OK is $119,360.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,400.00 and $129,700.00 per year, depending on experience, location, and employer.

What is a quantitative model validation analyst?

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 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 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 job categories do people searching Quantitative Model Validation Analyst jobs in Edmond, OK look for?

The top searched job categories for Quantitative Model Validation Analyst jobs in Edmond, OK are:

Quantitative Model Validation Analyst jobs near you

Sr. Manager of Analytics and Data Science

Oklahoma City, OK • On-site

Loves Travel Stops & Country Store
Gasoline Stations • 10K+ employees

5.8

Company rating: 5.8 out of 10

Based on 800 frontline employees who took The Breakroom Quiz

402nd of 738 rated retailers

People enjoy working here

Recommended by parents

Respectful managers

Learn more about Loves Travel Stops & Country Storeexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 days ago

Job description

Req ID: 484195
Benefits: * Fuel Your Growth with Love's - company funded tuition assistance * Paid Time Off * 401(k) - 100% Match up to 5% * Medical/Dental/Vision Insurance the first of the month after 30 days * Competitive Pay * Career Development *
Welcome to Love's: The Senior Manager of Analytics & Data Science leads teams of analytics and data science professionals responsible for delivering enterprise-wide insights, advanced analytics, and scalable solutions that drive strategic decision-making across the organization. This leader partners closely with business and technology stakeholders to identify opportunities, solve complex business challenges, and deliver measurable business impact through data.
Job Functions:
Drive Strategic Decision-Making Through Analytics
  • Partner with leaders across the organization to identify opportunities where analytics can improve business performance and support strategic objectives
  • Translate complex business questions into actionable analytical approaches and measurable outcomes
  • Deliver insights and recommendations that influence decision-making at all levels of the organization
  • Promote the use of data and analytics as strategic assets across the enterprise

Advanced Analytics & Solution Delivery
  • Oversees the entire lifecycle of analytics projects, including requirement gathering, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI-enabled solutions
  • Ensures analytical solutions are scalable, actionable, and aligned to business objectives while delivering measurable business value
  • Establishes best practices that drive consistency, quality, and adoption across analytics initiatives
  • Guides teams in balancing technical rigor with practical business application to maximize organizational impact

Team Leadership & Development
  • Build and scale a high-performing data science & analytics organization, defining roles, career paths, and operating norms that attract and retain top analytical talent.
  • Lead a team of data scientists, seen as trusted advisors, known for proactive insights and creating thought leadership.
  • Foster a culture of curiosity, accountability, analytical rigor, experimentation, and continuous improvement.
  • Collaborate cross-functionally with Customer Experience, FP&A, and Data Engineering to deliver comprehensive solutions.
  • Provide coaching, performance management, and career development opportunities that support employee growth and engagement
  • Establish clear priorities and create an environment that enables teams to perform at their highest level

Strategic Analytics Roadmap
  • Define and evolve the enterprise analytics roadmap in alignment with organizational priorities
  • Evaluate and prioritize initiatives to maximize business impact and resource effectiveness
  • Balance short-term business needs with long-term capability development
  • Identify opportunities to expand analytics capabilities and increase organizational value

Strengthen Enterprise Partnerships
  • Develop trusted relationships with stakeholders across operations, finance, marketing, merchandising, customer experience, technology, and other business functions
  • Align analytics investments with enterprise priorities and strategic goals
  • Facilitate collaboration between analytics, technology, and business teams to maximize impact
  • Effectively communicate complex analytical concepts to technical and non-technical audiences, including senior leadership

Data Governance & Quality
  • Partner with technology and data teams to improve data quality, governance, accessibility, and trustworthiness
  • Advocate for data standards and best practices that support enterprise analytics
  • Ensure analytical solutions are built on reliable, well-governed data foundations
  • Promote confidence and trust in analytical outputs across the organization

Innovation & Continuous Improvement
  • Champion the adoption of emerging analytics, automation, and AI-enabled capabilities that improve business outcomes, accelerate insight generation, and enhance team effectiveness
  • Encourage experimentation and continuous improvement in analytical approaches and methodologies
  • Partner with technology teams to evaluate and apply emerging capabilities that enhance analytics effectiveness
  • Maintain awareness of industry trends and identify opportunities to create value through innovation

Experience and Qualifications:
  • Bachelor's degree required in a quantitative or technical field (e.g., data science, statistics, mathematics, computer science, economics, engineering, or operations research); Master's or PhD strongly preferred
  • 8+ years of progressive experience in data science, advanced analytics, or quantitative modeling, including hands-on delivery of machine learning and statistical models in a production environment
  • 3+ years of direct people-leadership experience managing and developing teams of data scientists and analysts
  • Demonstrated track record of translating ambiguous business problems into analytical solutions that drive measurable, enterprise-level impact
  • Experience partnering with executive and cross-functional stakeholders to set strategy and influence decisions without direct authority
  • Retail, fuel, hospitality, or large-scale consumer/operations experience preferred

Skills and Physical Demands:
  • Deep proficiency in machine learning, statistical modeling, experimentation/A/B testing, forecasting, and optimization techniques
  • Strong programming and data fluency with Python and/or R, advanced SQL, and modern data platforms (e.g., Snowflake, Databricks, or comparable cloud data warehouses)
  • Working knowledge of cloud environments (AWS, Azure, or GCP) and MLOps practices for deploying, monitoring, and maintaining models at scale
  • Proficiency with BI and visualization tools (e.g., Tableau, Power BI, Sigma) to communicate insight clearly to business audiences
  • Familiarity with generative AI and large language model applications and their responsible, value-driven use in the enterprise
  • Proven ability to build, scale, mentor, and retain high-performing technical teams
  • Strong business acumen with the ability to connect analytical work to financial and operational outcomes
  • Excellent written and verbal communication skills, including the ability to make complex concepts clear and compelling to senior, non-technical leadership.
  • Skilled at prioritization, roadmap planning, and resource management across competing demands
  • Self-directed leader who thrives in a fast-moving, collaborative, and evolving environment

Our Culture:
Fueling customers' journeys since 1964, innovation leads the way for this family-owned and operated business headquartered in Oklahoma City. With nearly 40,000 team members, travel stops are the core business along with products and services that provide value for professional drivers, fleets, traveling public, RVers, alternative energy and wholesale fuel customers. Giving back to communities and an inclusive workplace are hallmarks of the award-winning culture.
Love's is an Equal Opportunity Employer. Veterans encouraged to apply.

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