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Model Validation Remote Jobs (NOW HIRING)

Hexion Inc.

Lead Data Scientist - US Remote

... model validation, performance monitoring, reproducibility, and documentation. • Partner with Supply Chain & Procurement leadership, Manufacturing Ops, Process Engineering, Demand Planning, and IT ...

Intersect

Microgrid Validation Lead

Charleston, WV · Remote

... flexible remote culture. Microgrid Validation Engineer About This Role As part of Intersect ... Analyze field operating data to improve simulation models and identify edge cases that require ...

Experian

$81K - $107K/yr

Develop, validate, and optimize statistical and machine learning models, including regression and ... Flexible work environment, ability to work remote, hybrid or in-office. * Flexible time off ...

Intersect

Microgrid Validation Engineer

... flexible remote culture. Microgrid Validation Engineer About This Role As part of Intersect ... Familiarity with simulation and modeling tools such as Simulink, Modelica, or similar platforms.

Intersect

Microgrid Validation Lead

... flexible remote culture. Microgrid Validation Engineer About This Role As part of Intersect ... Analyze field operating data to improve simulation models and identify edge cases that require ...

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Model Validation Remote information

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How much do model validation remote jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for model validation remote in the United States is $52.00, according to ZipRecruiter salary data. Most workers in this role earn between $39.42 and $63.22 per hour, depending on experience, location, and employer.

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.
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Model Validation Remote jobs near you
Ophthalmologist (Medical Data Labeling Specialist)

Ophthalmologist (Medical Data Labeling Specialist)

Saviance

Boston, MA • Remote

Other

Posted 25 days ago

Job description

Ophthalmologist (Medical Data Labeling Specialist)
Location: India, Remote
Duration: Ongoing Part-Time
About BigRio
BigRio is a Boston-based, remote-first technology consulting firm specializing in advanced data and software solutions. We partner with forward-thinking organizations to deliver scalable, cost-effective, and innovative technology, with particular expertise in AI/ML, data engineering, and cloud-native applications. Our clients span healthcare, life sciences, government, and enterprise sectors, and we are known for our ability to tackle complex challenges with cutting-edge solutions.
About Job:
This role leverages the clinical expertise of an ophthalmologist to accurately annotate and label medical data, primarily images and structured clinical data related to eye health, for the development and refinement of artificial intelligence (AI) and machine learning (ML) models in ophthalmology.
Responsibilities
Key responsibilities include:
  • Data Annotation: Reviewing and annotating various ophthalmic data like fundus images, Optical Coherence Tomography (OCT) scans, and other visual data, identifying anatomical structures and disease markers.
  • Adherence to Protocols: Applying standardized grading protocols consistently for accurate and consistent labeling.
  • Quality Control & Feedback: Participating in calibration sessions and reviews to maintain annotation consistency.
  • Collaboration: Working with AI engineers and data scientists to ensure the clinical validity of guidelines.
  • AI Model Validation: Validating AI model outputs for clinical accuracy and safety.
  • Patient Education Material Development (potential): Possibly creating or reviewing materials for AI/ML algorithms to provide accurate patient education.
  • Privacy and Security: Ensuring compliance with patient privacy and data security policies, like HIPAA.
Qualifications
Essential qualifications typically include:
  • Ophthalmologist (MBBS) with at least 1-2 years of clinical experience.
  • Extensive Clinical Knowledge: In-depth understanding of various eye conditions.
  • Experience in Clinical Data Review: Familiarity with medical record documentation.
  • Attention to Detail: Commitment to accurate annotation.
  • Communication Skills: Excellent communication skills, both written and verbal, in English.
  • Teamwork: Ability to collaborate effectively with a multidisciplinary team.
Required skills often include:
  • Medical Image Annotation: Proficiency in using annotation tools to delineate structures and pathologies
  • Data Interpretation and Assessment: Skill in interpreting data related to medical products and AI model performance.
  • Problem Solving: Ability to identify challenges and recommend solutions.
  • Adaptability: Ability to adapt to varying image resolutions and file formats.

This role offers a unique opportunity to contribute to the development of AI tools that can improve eye health and patient care on a wider scale.
Saviance logo

About Saviance

Sourced by ZipRecruiter

Saviance is a modern consulting firm providing a variety of professional services to its clients in the US. We bring twenty three years of experience to the table. Our consultants are qualified experts and extremely talented. We understand the business behind the technology, and work with many of the top Fortune 100 companies and provide innovative, scalable, robust and secure solutions. At the forefront of the Staffing and IT Solutions industry, Saviance is certified by NMSDC as a Tier 1, Minority Business Enterprise (MBE) . We are a self- certified Small Business and self- certified Woman Owned Business committed to maximizing global workforce solutions on behalf of our clients, empowering businesses and talent through applied human intelligence. We are a Diversity Supplier with global reach specializing in a business services blend of talent, technology, and a relentless commitment to customer success. It’s our diversity that’s acts as a core component of our culture, our approach to business, and the opportunities we provide to our clients and our employees.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

East Rutherford, NJ, US

Year founded

1999

Social media

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