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Senior Model Risk Management Jobs in Ohio (NOW HIRING)

Sabio infotech

Sr. Machine Learning Engineer

Cincinnati, OH · On-site

$100K - $137K/yr

Sr. Machince Learning Engineer Location: Cincinnati OH (Hybrid - 3 Days Onsite) Duration: 1+ Year ... AI, model explainability, governance, and risk management concepts. · Proficiency in Python and ...

Scotiabank

Senior AI Engineer

Toronto, OH · On-site

$93K - $128K/yr

... • Model risk management requirements • Privacy and consent controls • Responsible AI ... • Mentor senior and mid‑level engineers, raising the overall technical bar across AI ...

Alpha Generation LLC

Sr. Risk Analyst

Middletown, OH · On-site

$80 - $110/hr

Reporting to the Director, Risk Management, the Sr. Analyst, Risk will provide analysis, evaluate ... Provide model development for pricing, valuation, and risk metrics using historical and forecast ...

New

PNC Bank

LOB Risk Spec Sr

Strongsville, OH · On-site

Executes and enhances Line of Business risk management programs to support business and regulatory ... Risk Quantification Responsibilities Technology Loss Modeling Develops and enhances technology loss ...

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Senior Model Risk Management information

What is the difference between Senior Model Risk Management vs Model Validation Analyst?

AspectSenior Model Risk ManagementModel Validation Analyst
CredentialsAdvanced degrees in finance, statistics, or related fields; certifications like FRM or CFASimilar credentials; often holds CFA, FRM, or related certifications
Work EnvironmentStrategic oversight, risk assessment, policy development within financial institutionsHands-on model testing, validation, and documentation in quantitative teams
Industry UsageUsed across banking, insurance, asset management for risk governancePrimarily in banking and financial services for model validation roles

While both roles require quantitative expertise and relevant certifications, Senior Model Risk Management focuses on overseeing and managing model risks at a strategic level, whereas Model Validation Analysts concentrate on testing and validating models to ensure accuracy and compliance.

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The most popular types of Model Risk Management jobs in Ohio are:

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Senior Model Risk Management jobs near you

Sr. Machine Learning Engineer

Sabio infotech

Cincinnati, OH • On-site

$100K - $137K/yr

Other

Posted 8 days ago

Job description

Sr. Machince Learning Engineer
Location: Cincinnati OH (Hybrid - 3 Days Onsite)
Duration: 1+ Year
 
Key Responsibilities
· Design, develop, deploy, and maintain scalable machine learning and Generative AI solutions with a focus on reliability, performance, security, and business value.
· Champion an automation-first approach to software and AI engineering, identifying opportunities to improve operational efficiency and reduce manual processes.
· Build and operationalize machine learning models and AI-enabled applications throughout the entire model lifecycle, from experimentation to production deployment and monitoring.
· Develop and deploy Generative AI applications in production environments, preferably within financial services or other highly regulated industries.
· Apply and advocate Responsible AI principles, ensuring solutions meet requirements for fairness, explainability, transparency, privacy, security, and compliance.
· Perform model risk evaluations, complete required governance documentation and questionnaires, and partner with stakeholders to address and remediate identified risks.
· Establish and maintain frameworks for MLOps, model lifecycle management, monitoring, validation, version control, auditability, and AI governance.
· Collaborate with Risk, Compliance, Information Security, and business partners to ensure machine learning solutions meet enterprise and regulatory standards.
· Implement CI/CD pipelines, automated testing, model monitoring, observability, and production support processes for machine learning applications.
· Evaluate emerging machine learning and AI technologies and recommend appropriate adoption strategies.
· Mentor team members on best practices in machine learning engineering, MLOps, Responsible AI, and production AI systems.
 
Required Qualifications
· Extensive experience designing, developing, and deploying machine learning solutions in production environments.
· Hands-on experience developing and deploying Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and modern AI development frameworks.
· Strong understanding of machine learning model development, feature engineering, model evaluation, performance optimization, and model monitoring.
· Experience conducting model risk assessments and supporting governance, compliance, and validation requirements within regulated environments.
· Practical experience implementing MLOps practices including model deployment, versioning, monitoring, automated retraining, and CI/CD pipelines.
· Strong understanding of Responsible AI, model explainability, governance, and risk management concepts.
· Proficiency in Python and modern machine learning ecosystems, including frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, or equivalent technologies.
· Strong communication, problem-solving, and stakeholder management skills.

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