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Model Validation Remote Jobs in Ohio (NOW HIRING)

... valid state licenses or equivalent school psychologist certification * Active DOE licensure * 1 ... Evaluations will be compensated on a component billing model that is separate from the hourly rate

Oracle Developer (Remote)

Columbus, OH ยท Remote

$54.50 - $67.75/hr

... modeling. * Work with users to define existing or new system scope and objectives. * Provide ... Evaluate code to ensure it is valid, meets industry standards and is compatible with devices or ...

Oracle Developer (Remote)

Columbus, OH ยท On-site +1

$54.50 - $67.75/hr

... modeling. * Work with users to define existing or new system scope and objectives. * Provide ... Evaluate code to ensure it is valid, meets industry standards and is compatible with devices or ...

Oracle Developer (Remote)

Columbus, OH ยท Remote

$54.50 - $67.75/hr

... modeling. * Work with users to define existing or new system scope and objectives. * Provide ... Evaluate code to ensure it is valid, meets industry standards and is compatible with devices or ...

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Model Validation Remote information

What is the difference between Model Validation Remote vs Model Validation on-site?

AspectModel Validation RemoteModel Validation on-site
Work EnvironmentRemote, home-basedOn-site, office or client location
Required CredentialsSimilar certifications, e.g., CFA, FRM, or relatedSame as remote, often with additional in-person requirements
Industry UsageFinancial institutions, banks, asset managersSame industries, with in-person collaboration
Work FlexibilityHigh, flexible hours and locationLess flexible, fixed hours and location

Both remote and on-site model validation roles require similar credentials and industry knowledge. The main difference lies in the work environment and flexibility, with remote positions offering greater convenience and location independence, while on-site roles facilitate direct collaboration and immediate access to resources.

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

To thrive as a Model Validation Remote, you need a strong background in quantitative disciplines such as mathematics, statistics, or finance, typically supported by a relevant degree. Proficiency with statistical software (like SAS, R, or Python), model risk management frameworks, and familiarity with regulatory guidelines (such as SR 11-7) are commonly required. Analytical thinking, attention to detail, and strong written communication are crucial soft skills in this role. These skills ensure accurate model assessments, regulatory compliance, and effective communication of complex findings to stakeholders.

What is model validation in a remote job context?

Model validation, especially in a remote setting, involves evaluating and verifying the accuracy, performance, and reliability of statistical or machine learning models from a location outside of a traditional office. Professionals in this role typically assess whether models meet regulatory requirements, function as intended, and are free from biases or errors. Remote model validators use various tools and techniques to conduct tests, write reports, and communicate findings with stakeholders via digital platforms. This work is essential in sectors like finance, insurance, and tech, where robust models drive critical decisions. Successful remote model validation requires strong analytical skills, clear communication, and proficiency with data analysis tools.

What are some common challenges faced by professionals in remote model validation roles, and how can they be addressed?

Remote model validation professionals often encounter challenges such as maintaining clear communication with model developers and stakeholders, accessing secure data environments, and staying updated with evolving regulatory standards. To address these, it's important to leverage robust collaboration tools, schedule regular check-ins with cross-functional teams, and participate in ongoing training or knowledge-sharing sessions. Establishing clear documentation protocols and ensuring secure remote access to necessary data can also help maintain productivity and compliance.
What cities in Ohio are hiring for Model Validation Remote jobs? Cities in Ohio with the most Model Validation Remote job openings:

Lead Data Scientist - US Remote

Hexion Careers

Columbus, OH โ€ข On-site, Remote

Full-time

Posted 26 days ago


Job description

Company Overview
ย 

Imagine Everything. Build the Future with Hexion.

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progressโ€”developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.

This is where bold thinkers, problem-solvers, and innovators come together to shape whatโ€™s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.

We donโ€™t follow the status quoโ€”we challenge it, disrupt it, and improve it.ย Every role at Hexion is part of something bigger.

We invest in innovation, sustainability, and continuous developmentโ€”equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Your Future Starts Here. ย 

If youโ€™re ready to push limits, reimagine whatโ€™s possible, and create the extraordinary, Hexion is where you belong.ย 

Anything is possible when you imagine everything.ย 

Job Responsibilities
  • Lead complex data science and machine learning initiatives supporting supply chain, manufacturing operations, capacity planning, demand forecasting, and operational decision-making.ย 
  • Design, develop, and own advanced ML solutions โ€” including predictive models, time-series forecasting, optimization, and decision-support systems โ€” scoped to supply chain and manufacturing use cases.ย 
  • Build, train, evaluate, and interpret machine learning models (regression, classification, clustering, forecasting) to quantify supply chain drivers, surface optimization opportunities, and improve operational outcomes.ย 
  • Develop and operationalize analytics and ML solutions using Databricks (Python / SQL / PySpark) for large-scale data processing, model development, and experimentation.ย 
  • Design and build multi-agent AI systems โ€” including orchestrator-executor architectures, tool-calling agents, and RAG-based decision support โ€” using frameworks such as Azure AI Foundry, AutoGen, Semantic Kernel, or LangChain/LangGraph.ย 
  • Implement and extend solutions using the MCP to enable AI agents to access and act on enterprise data systems in supply chain and manufacturing contexts.ย 
  • Apply data science best practices including feature engineering, model validation, performance monitoring, reproducibility, and documentation.ย 
  • Partner with Supply Chain & Procurement leadership, Manufacturing Ops, Process Engineering, Demand Planning, and IT to translate ambiguous business problems into structured ML and AI approaches.ย 
  • Develop and maintain self-service, automated, and AI-enabled analytics workflows that reduce manual effort and improve decision latency.ย 
  • Leverage Azure AI Foundry, Microsoft Copilot Studio, and Microsoft 365 Copilot extensibility to prototype and deploy AI-powered analytics and agent-based decision-support tools.ย 
  • Produce executive-ready insights through clear storytelling, visualizations, and recommendations using Power BI or embedded analytics.ย 
  • Set technical direction, establish reusable ML and AI frameworks, and mentor junior and mid-level data scientists across the team.ย 
  • Ensure high standards of data quality, governance, model validation, and explainability.ย 
Minimum Qualifications

Education & Experience (one of the following):ย 

  • Masterโ€™s degree in Statistics, Mathematics, Industrial Engineering, Data Science, Computer Science, Engineering, or a related quantitative field with 5+ years of relevant data science/analytics experience, ORย 
  • Bachelorโ€™s degree in the same or related fields with 8+ years of relevant data science / analytics experience.ย 


Technical:ย 

  • Demonstrated track record delivering advanced ML and data science solutions in supply chain, manufacturing, or industrial domains.ย 
  • Strong hands-on experience with machine learning and statistical modeling โ€” development, interpretation, and operational business application.ย 
  • Strong proficiency in Databricks (Python, SQL, PySpark, Delta Lake).ย 
  • Hands-on experience with the MCP โ€” building or consuming MCP servers/clients to connect AI agents to enterprise data systems, APIs, or ERP modules.ย 
  • Hands-on experience with multi-agent system design โ€” architecting multi-agent systems using AutoGen, Semantic Kernel, LangChain/LangGraph, or Azure AI Agent Service; orchestrator-executor patterns, tool calling, memory management, and agent coordination.ย 
  • Compulsory โ€” must have hands-on experience with one or more of the following:ย 
    • Azure AI Foundryย 
    • Microsoft Copilot Studioย 
    • Microsoft 365 Copilot extensibilityย 
    • Microsoft Power Platform (Power Automate, Power BI)ย 
  • Ability to translate complex business problems into ML / AI solutions and communicate findings to both technical and executive audiences.ย 
  • Strong stakeholder management and cross-functional collaboration skills.ย 
Preferred Qualifications
  • Experience operationalizing ML models into production in supply chain or manufacturing environments.ย 
  • Familiarity with SAP ECC / S/4HANA supply chain and manufacturing modules (MM, PP, PM, SD).ย 
  • Strong Power BI experience โ€” semantic modeling, performance optimization, executive dashboard design.ย 
  • Exposure to MLOps on Azure (Azure ML, MLflow, Databricks Asset Bundles, CI/CD for analytics artifacts).ย 
  • Experience designing operational KPI frameworks (MAPE, OTIF, service level, OEE, downtime).ย 
  • Experience with statistical / simulation methods (Monte Carlo, scenario analysis, sensitivity analysis) applied to operations and supply chain.ย 
  • Familiarity with Palantir Foundry (pipelines, ontology, Workshop, AIP).ย 
  • Proven experience mentoring data scientists or leading end-to-end analytics initiatives.ย 
  • Familiarity with cloud-native data architectures and governed data platforms.ย 
Other
ย 

We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.

To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age. ย Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.