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Head Of Model Risk Management Jobs in Oregon (NOW HIRING)

Atos

Head of AI

OR · On-site +1

Position : Head of Artificial Intelligence Role Summary The Head of Artificial Intelligence ... model risk management). * Partner with security, legal, and compliance teams to ensure AI solutions ...

Atos

Head of AI

OR · On-site +1

Position : Head of Artificial Intelligence Role Summary The Head of Artificial Intelligence ... model risk management). * Partner with security, legal, and compliance teams to ensure AI solutions ...

Cotiviti

Determine aspects of model drift and related data drift for the purpose of model risk management (MRM) to both reduce risk and also find opportunities to drive new revenue growth and innovation.

Cotiviti

Determine aspects of model drift and related data drift for the purpose of model risk management (MRM) to both reduce risk and also find opportunities to drive new revenue growth and innovation.

Upstart

OR · On-site

... to the Head of Secured Lending. You will lead a small team of analysts and partner closely with Credit Risk, Capital Markets, Model Risk Management, Product, Engineering, Compliance, Legal ...

Upstart

OR · On-site

... to the Head of Secured Lending. You will lead a small team of analysts and partner closely with Credit Risk, Capital Markets, Model Risk Management, Product, Engineering, Compliance, Legal ...

Treliant LLC

Consultant, Risk Management

$75 - $150/hr

... model risk, and third-party risk management. --- Primary Location: Remote Primary Location Salary ... Qualifications * 5 to 8 years of experience at a financial services institution, banking, or ...

M0

OR

M0 is seeking a sharp, execution-focused Head of Security & Risk to build and own the information ... Build and Own Enterprise Risk Management : Build M0's enterprise risk program from scratch. Cover ...

Upstart

Credit Risk Manager

OR · On-site +1

Partner with peers in Model Risk Management and Fair Lending on second line teams. * Prepare and ... Provide independent challenge and oversight of credit policies, underwriting performance, and risk ...

Upstart

OR · On-site

This role reports to the head of third party and technology risk and manages a team of two ... model-intensive operating environment Position location This role is available in the following ...

Groups Recover Together, Inc.

... mix, clinical model, and strategic adjacencies. Pipeline & Origination. Build and manage a ... risk-adjusted returns in partnership with CFO. Execution. Negotiate LOIs, definitive agreements ...

Airspace

OR

Overview The Global Head of Pricing leads Airspace's pricing function, owning the models, processes ... model expectations * Ensuring pricing accuracy through close partnership with Yield Management Rate ...

Cencora

OR · On-site

Our team members are at the heart of everything we do. At Cencora, we are united in our ... Job Details The Director, Enterprise Risk Management is responsible for managing and maturing the ...

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All JobsHead Of Model Risk Management JobsHead Of Model Risk Management Jobs in Oregon

Head Of Model Risk Management information

See Oregon salary details

$57.1K

$151.4K

$274.9K

How much do head of model risk management jobs pay per year?

As of Jul 11, 2026, the average yearly pay for head of model risk management in Oregon is $151,387.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $177,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Head Of Model Risk Management, and why are they important?

To thrive as a Head Of Model Risk Management, you need deep quantitative expertise, advanced knowledge of risk management frameworks, and a strong background in finance or mathematics, often supported by advanced degrees such as a PhD or MSc. Familiarity with statistical software (like Python, R, or SAS), model validation tools, and regulatory compliance systems is typically required. Exceptional leadership, communication, and critical thinking skills are essential for effectively managing teams and presenting complex risk issues to stakeholders. These skills ensure robust oversight of model risk, regulatory compliance, and sound decision-making within financial institutions.

What is the difference between Head Of Model Risk Management vs Model Validation Manager?

AspectHead Of Model Risk ManagementModel Validation Manager
Primary FocusOversees overall model risk framework, governance, and strategyConducts independent validation and testing of models
ResponsibilitiesRisk oversight, policy development, senior stakeholder communicationModel testing, performance assessment, validation reports
CredentialsAdvanced degrees, certifications like FRM, CFA, or CAMS, experience in risk managementQuantitative background, certifications like CFA, FRM, strong modeling expertise
Work EnvironmentStrategic, leadership role within risk management teamsTechnical, analytical role focused on model validation tasks

The Head Of Model Risk Management oversees the entire model risk framework, focusing on strategy and governance, while the Model Validation Manager specializes in testing and validating individual models. Both roles require strong quantitative skills and relevant certifications, but differ in scope and responsibilities.

What are the main challenges faced by a Head of Model Risk Management in maintaining regulatory compliance?

A Head of Model Risk Management often faces the challenge of keeping up with evolving regulatory expectations and ensuring that all models used within the organization are compliant. This involves constantly monitoring regulatory updates, coordinating with various departments to implement necessary changes, and maintaining detailed documentation for audit purposes. Additionally, the role requires balancing the need for innovation in modeling techniques with the necessity of robust risk controls and transparent validation processes. Regular communication with risk, compliance, and audit teams is essential to address these challenges effectively.

What does a Head of Model Risk Management do?

A Head of Model Risk Management oversees the processes and teams responsible for identifying, assessing, and mitigating risks associated with financial and predictive models used within an organization. This role involves establishing and maintaining model risk frameworks, ensuring regulatory compliance, and leading model validation activities. They also coordinate with other departments to ensure the effective management and governance of all models, providing guidance on best practices and emerging risks. Ultimately, their goal is to minimize model-related losses and support sound decision-making across the business.
What are popular job titles related to Head Of Model Risk Management jobs in Oregon? For Head Of Model Risk Management jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Head Of Model Risk Management jobs in Oregon look for? The top searched job categories for Head Of Model Risk Management jobs in Oregon are:
What cities in Oregon are hiring for Head Of Model Risk Management jobs? Cities in Oregon with the most Head Of Model Risk Management job openings:
Head Of Model Risk Management jobs near you

Head of AI

Atos

OR • On-site, Remote

Other

Re-posted 6 days ago

Job description

About Atos Group

Atos Group is a global leader in digital transformation with c. 67,000 employees and annual revenue of c. 10 billion, operating in 61 countries under two brands - Atos for services and Eviden for products. European number one in cybersecurity, cloud and high performance computing, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is the brand under which Atos SE (Societas Europaea) operates. Atos SE is listed on Euronext Paris.

The purpose of Atos Group is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

  Position : Head of Artificial Intelligence Role Summary

The Head of Artificial Intelligence Practice (North America) leads strategy, growth, delivery excellence, and talent for the AI portfolio across U.S. and Canada. This executive role owns practice P&L, builds scalable offerings (GenAI, ML, data science, AI platforms, MLOps), and partners with sales and delivery leaders to expand revenue and customer impact across industries.

Reporting and Scope
  • Reports to: Head of Data & AI - North America
  • Direct reports: AI practice leadership team (solution leads, delivery leaders, architects), plus dotted-line matrix teams
  • Geography: United States and Canada (remote/hybrid depending on location)
  • Travel: Up to 25-40% (client sites, executive briefings, industry events)
Key Responsibilities        Practice strategy and roadmap
    • Define the North America AI practice strategy aligned to corporate goals and market demand.
    • Build and maintain a 12-24 month capability roadmap across GenAI, Agentic AI, applied ML, AI engineering, MLOps, and AI governance.
    • Identify strategic bets (industries, partnerships, platforms) and prioritize investments for impact and scale.
    • Lead the delivery team for AI across NA including building and managing talent and ensuring ulitization targets for the team
       Portfolio, offerings, and thought leadership
    • Support Head of Advisory and Global Teams with packaged offerings and accelerators (POCs-to-production playbooks, reference architectures, reusable components).
    • Work with Head of Innovation industry-specific solutions (e.g., banking, retail, healthcare, telecom, public sector) with measurable outcomes.
    • Represent the company externally through speaking, publishing, analyst briefings, and customer success stories.
       Go-to-market and revenue growth
    • Own pipeline and bookings targets for AI services in North America; partner with sales, alliances, and marketing.
    • Help Represent the solutioning for strategic pursuits, including executive-level proposal narratives, value cases, and pricing models.
    • Help support the partner ecosystem with hyperscalers and AI platform vendors; drive co-sell motions where applicable.
       Delivery excellence and customer outcomes
    • Ensure high-quality delivery across AI engagements, with strong governance, risk management, and stakeholder communication.
    • Standardize delivery methodology for AI programs (discovery, prototyping, productionization, monitoring, continuous improvement).
    • Drive customer adoption, measurable business value, and referenceability through disciplined success management.
       Talent, org design, and culture
    • Build and scale a high-performing AI team: hiring plans, skills frameworks, career paths, and mentorship.
    • Upskill broader delivery teams through training programs, communities of practice, and internal enablement.
    • Foster a culture of engineering rigor, responsible AI, collaboration, and continuous learning.
       Governance, security, and responsible AI
    • Establish responsible AI standards (privacy, security, bias mitigation, explainability, model risk management).
    • Partner with security, legal, and compliance teams to ensure AI solutions meet client and regulatory requirements.
    • Define and monitor AI practice quality standards, including data governance, model lifecycle controls, and audits.
       Financial management and operations
    • Help support the Head of Data and AI P&L: revenue, gross margin, utilization, bench, subcontractor mix, and investment planning.
    • Set operating rhythm: QBRs, forecast accuracy, capacity planning, and delivery health dashboards.
    • Optimize delivery model (onshore/nearshore/offshore) to meet client needs and margin targets.

Required Qualifications

  • 15+ years of experience in technology consulting, product engineering, or enterprise technology leadership, with 8+ years in AI/ML/GenAI leadership.
  • Proven track record building and scaling an AI practice or portfolio with P&L responsibility and measurable revenue growth.
  • Strong understanding of modern AI stack: GenAI (LLMs), Agentic AI, ML, data engineering, AI platforms, MLOps/LLMOps, and cloud services (AWS/Azure/GCP).
  • Demonstrated experience delivering AI solutions end-to-end: discovery to production, monitoring, and continuous improvement.
  • Executive presence with ability to influence EVP-level stakeholders and lead complex deal pursuits.
  • Experience leading multi-disciplinary teams (AI Architects, AI Engineers, data scientists, ML engineers, architects, product managers, delivery leaders).
  • Knowledge of responsible AI, security, and privacy requirements for enterprise AI implementations.
Preferred Qualifications
  • Experience in IT services/consulting organizations operating with global delivery models (onshore/nearshore/offshore).
  • Domain expertise in one or more regulated industries (financial services, healthcare, telecom, government).
  • Partnership experience with hyperscalers and AI platform vendors; co-sell and alliance management success.
  • Hands-on experience with AI solution architecture, including retrieval-augmented generation (RAG), vector databases, and agentic workflows.
  • Advanced degree in Computer Science, Engineering, Data Science, or related field; MBA a plus.
Core Competencies
  • Strategic leadership and business building
  • Consultative selling and executive stakeholder management
  • AI engineering rigor and delivery governance
  • Productization mindset (offerings, accelerators, repeatability)
  • Talent development and organizational design
  • Cross-functional collaboration in matrix environments
  • Strong communication: narrative building, proposals, and presentations
Tools and Technologies (Representative)
  • Cloud: AWS, Microsoft Azure, Google Cloud Platform
  • AI/ML: Agentic AI, Python, PyTorch/TensorFlow, scikit-learn, MLflow (or equivalent), feature stores
  • GenAI: LLM APIs and platforms, prompt engineering, RAG patterns, evaluation frameworks, guardrails
  • Data: SQL, modern data warehouses/lakehouse platforms, streaming where needed
  • MLOps/LLMOps: CI/CD for models, monitoring/observability, model registry, governance tooling
Work Environment
  • Remote or hybrid within North America; may require proximity to major client hubs.
  • Travel expectation up to 25-40% based on client needs and business development cycles.
  • This role may require occasional work outside standard business hours to support executive meetings across time zones.
Equal Opportunity

The organization is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.

Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment. 


Choose your future. Choose Atos.

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