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Model Validation Manager Jobs in Oregon (NOW HIRING)

Staff Machine Learning Model Risk Specialist

OR · On-site +1

$98K/yr

Internship or project experience related to model risk management, model validation, machine learning, or data science. * Basic understanding of AI/ML methodologies such as tree-based models and ...

Validation Engineer

Salem, OR · On-site +1

$134K - $184K/yr

Validation Engineer Join us to do the best work of your career and make a profound social impact as ... system management console solutions. * Knowledge of cloud/big data software stack models and ...

Validation Engineer 2

Bend, OR · On-site

$70.92 - $99.29/hr

Validation Engineer 2 CSV/CQV Specialist Location: 1201 NW Wall Street, Bend, OR 97703 Work Model ... Hiring Manager Priorities * Immediate need due to a significant CQV validation backlog . * Strong ...

Validation Engineer

Portland, OR · On-site

$87K - $94K/yr

... Testing & Vendor Management - Support execution of design reviews, equipment shakedown ... models company values - Seeks out breakthrough opportunities #LI-MV1 $87,152 - $94,600 a year ...

... Testing & Vendor Management - Support execution of design reviews, equipment shakedown ... models company values - Seeks out breakthrough opportunities #LI-MV1 $87,152 - $94,600 a year ...

... Testing & Vendor Management - Support execution of design reviews, equipment shakedown ... models company values - Seeks out breakthrough opportunities #LI-MV1 Average base salary range ...

Responsible for procurement of necessary materials, manages time and assigned work effectively ... Able to validate critical features and dimensions using hand metrology equipment. * Must possess a ...

Responsible for procurement of necessary materials, manages time and assigned work effectively ... Able to validate critical features and dimensions using hand metrology equipment. * Must possess a ...

Oversee end-to-end delivery of AI solutions, including data readiness, model validation, deployment ... Manage staffing, workload balancing, and performance. * Foster a high-performing, client-centric ...

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Design automated workflows for prompt testing, retrieval evaluation, AI system validation, and performance benchmarking. * Develop internal tools for prompt management, model experimentation, AI ...

Strong understanding of contact center Quality Management processes, evaluation frameworks, and scoring methodologies. Experience selecting and analyzing call/interaction samples for model validation ...

Algorithm Developer IV

Portland, OR · On-site

$160K - $220K/yr

... Management, and Core Algorithm teams Translate customer challenges into modeling and algorithm ... model validation Spectra and signal analysis reports DOE recommendations and conclusions ...

Work closely with Application, Systems, AE, Product Management, and Core Algorithm teams ... Simulation reports and model validation * Spectra and signal analysis reports * DOE recommendations ...

Algorithm Developer IV

Portland, OR · On-site

$160K - $220K/yr

Work closely with Application, Systems, AE, Product Management, and Core Algorithm teams ... Simulation reports and model validation * Spectra and signal analysis reports * DOE recommendations ...

Familiarity with design modeling and benchmarking tools. Preferred Qualifications * Validation experience in one or more of the following: * Functional: Core, Memory Power Management, Manageability ...

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Showing results 1-20

Model Validation Manager information

See Oregon salary details

$50.2K

$111.5K

$169.7K

How much do model validation manager jobs pay per year?

As of Aug 31, 2026, the average yearly pay for model validation manager in Oregon is $111,454.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,800.00 and $139,600.00 per year, depending on experience, location, and employer.

What does a model validation manager do?

A Model Validation Manager is responsible for overseeing the validation of financial, risk, or predictive models within an organization. Their primary duties include ensuring that models are accurate, reliable, and compliant with regulatory requirements. They lead teams that assess model performance, identify potential weaknesses, and recommend improvements. This role helps maintain the integrity of models used in decision-making processes, particularly in industries like banking and finance.

What skills and qualifications are needed to be a model validation manager?

To thrive as a Model Validation Manager, you need strong quantitative analysis skills, knowledge of risk management, and an advanced degree in mathematics, statistics, finance, or a related field. Familiarity with technical tools such as Python, R, SAS, and model risk management frameworks, as well as experience with regulatory compliance, is typically required. Exceptional problem-solving, communication, and stakeholder management abilities are important soft skills for this role. These skills ensure effective validation of financial models, regulatory compliance, and clear communication of complex findings to non-technical audiences.

How does a model validation manager collaborate with other teams during the model validation process?

A Model Validation Manager works closely with model developers, risk management teams, and internal audit to ensure models meet regulatory and business standards. Collaboration often involves reviewing model documentation, discussing model assumptions and methodologies, and providing feedback for improvements. Effective cross-functional communication is essential, as validation managers must balance technical analysis with regulatory compliance and business objectives. Regular meetings and clear reporting lines help facilitate this collaboration, ensuring that model risks are identified and addressed promptly.

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

AspectModel Validation ManagerQuantitative Analyst
CredentialsTypically requires advanced degrees in finance, mathematics, or statistics; certifications like CFA or FRM are commonOften holds degrees in finance, economics, or mathematics; certifications like CFA are also common
Work EnvironmentWorks in risk management, model validation teams within banks or financial institutionsWorks in trading, investment analysis, or risk departments within financial firms
Industry UsagePrimarily in banking, asset management, and financial services for model risk assessmentAcross investment firms, hedge funds, and banks for market analysis and trading strategies

The Model Validation Manager focuses on reviewing and validating financial models to ensure accuracy and compliance, often working within risk management teams. In contrast, a Quantitative Analyst develops and applies mathematical models for trading, investment, or risk purposes. While both roles require strong quantitative skills and similar credentials, their core responsibilities and work environments differ significantly.

What are the most commonly searched types of Model Validation jobs in Oregon?

The most popular types of Model Validation jobs in Oregon are:

What job categories do people searching Model Validation Manager jobs in Oregon look for?

The top searched job categories for Model Validation Manager jobs in Oregon are:

What cities in Oregon are hiring for Model Validation Manager jobs?

Cities in Oregon with the most Model Validation Manager job openings:

Infographic showing various Model Validation Manager job openings in Oregon as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $111,454 per year, or $53.6 per hour.

Staff Machine Learning Model Risk Specialist

OR • On-site, Remote


Upstart

7.6

Company rating: 7.6 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Good employer

Respectful managers

Good training


$98K/yr

Full-time

Posted 13 days ago


Job description

The Team: 

Upstart's Model Risk team is responsible for ensuring that the risk of models - including all models impacting the new Upstart Bank - is well-understood, monitored, and mitigated. For years, machine learning (ML) models have been the key, differentiating technology at Upstart and an exciting area of focus for the team, but we are also expanding our scope to include all modeling methodologies and Generative AI applications across the Bank. This work is essential for Upstart's internal risk management, ensuring that our models help us make better decisions and maintain credibility with external stakeholders such as our regulators and capital providers. The team's focus is on articulating sound model risk management principles and implementing them in collaboration with our peers on Upstart's Risk and Machine Learning teams. This work also includes explaining our models to stakeholders, supporting external validations, and conducting analyses to reinforce our goals.

As a Staff Model Risk Specialist at Upstart, you will independently execute core components of the model risk management program supporting Upstart Bank. You will oversee risk across a diverse and growing inventory of models and Generative AI applications, including sophisticated machine learning models used in lending and other models supporting areas such as fraud, compliance, finance, capital and liquidity, servicing, and operational risk.

This presents a unique opportunity to help build a comprehensive model risk management program for a new bank. You will evaluate model and GenAI application documentation, monitoring, governance, and risk assessments while partnering with developers, business sponsors, and risk stakeholders to identify and address emerging risks. You will apply a risk-based approach across technologies that range from traditional statistical methods to advanced machine learning and GenAI systems, adapting your review to their different purposes, complexities, and risk profiles. You will also translate complex technical concepts into clear, decision-useful information for audiences with varying levels of technical expertise.

How you'll make an impact

  • Partner with Machine Learning teams, GenAI application developers, business sponsors, and other stakeholders to maintain accurate inventories, risk assessments, documentation, monitoring reports, and supporting governance materials for models and GenAI applications affecting Upstart Bank.
  • Review methodologies, assumptions, data inputs, system designs, performance measures, controls, and limitations to provide effective challenge and identify areas requiring further analysis or remediation.
  • Apply a risk-based approach to evaluate a broad range of quantitative methods and technologies, from traditional statistical and financial models to complex machine learning models and GenAI applications.
  • Conduct and document model risk assessments, monitoring reviews, and targeted quantitative analyses that support internal policies and regulatory expectations.
  • Help develop practical governance approaches for new and rapidly evolving technologies, particularly machine learning and GenAI applications for which risks, evaluation methods, and industry practices continue to evolve.
  • Respond to model- and GenAI-related questions from regulators, lending partners, and other external stakeholders in collaboration with Machine Learning, business teams, Legal, Compliance, and partner-facing teams.
  • Track model risk issues, remediation plans, program goals, and emerging risks, escalating material findings and recommending practical improvements as the Bank's model inventory and use cases continue to expand.

Minimum Qualifications 

  • Master's degree in quantitative field such as finance, mathematics, economics, statistics or a related discipline
  • 4+ years of experience in model risk management, model validation, model governance, machine learning, data science, quantitative risk, AI governance, or a related technical risk function.
  • Internship or project experience related to model risk management, model validation, machine learning, or data science.
  • Basic understanding of AI/ML methodologies such as tree-based models and neural networks.
  • General familiarity with GenAI applications.
  • Experience coding in R, Python, or similar languages such as Matlab

Preferred Qualifications

  • PhD in a quantitative field of study such as statistics, econometrics, finance, mathematics; or a related discipline
  • 5+ years of experience in model risk management or model governance, or related fields such as ML and Data Science, Risk, Trust and Safety, or Technical Writing
  • Familiarity with GenAI applications, including evaluation approaches, prompt and system design, retrieval-augmented generation, tool use, guardrails, and ongoing monitoring.
  • Experience assessing models used outside of credit underwriting, such as models supporting fraud, compliance, finance, capital and liquidity, servicing, operational risk, or financial reporting.
  • Strong communication skills: ability to adapt technical information to varying needs and audiences, and managing trade-offs such as providing modeling detail while protecting intellectual property
  • Proactive mindset with the ability to take initiative 
  • Understanding of advanced AI/ML topics such as model monitoring, fairness, and explainability
  • Advanced coding skills in R, Python, and SQL, and experience using Git
  • Interest in or knowledge of consumer lending, credit risk, model fairness, explainability, or the use of machine learning and GenAI in a regulated environment.

Position location This role is available in the following locations: Remote

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions' cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

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#LI-MidSenior


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