Model Validator

at  Ninja Analytics

Model Validator
Please note: this position is contingent upon award
We are seeking a highly analytical and detail-oriented Model Validator to join our team. In this role, you will be responsible for independently validating models used across various business functions, ensuring their accuracy, robustness, and compliance with regulatory standards. You will work closely with model developers, risk managers, and other stakeholders to assess and improve model performance and reliability.
Ninja Analytics is an information technology company that provides analytical and software development services to companies with AML, fraud detection, trade surveillance, and systems integration, documentation, and governance needs. We provide an exciting, challenging, and rewarding work experience. We select people based on ability, attitude, character, skill, and training without discrimination regarding age, color, credit, marital status, national origin, political belief, race, religious beliefs, or a disability that does not prohibit performance of essential job functions. Ninja employees have competitive wages, paid time off and holidays, as well as health and welfare benefits. Our work environment is comfortable, orderly, safe, and often remote. Lastly, Ninja Analytics respects individual rights, and treats all employees with courtesy and consideration. We are a certified Small, Woman-Owned Business (WOSB).

Key Responsibilities:

• Model Validation:
• Conduct comprehensive validation of models used for risk management, financial forecasting, pricing, and other business applications.
• Evaluate model assumptions, methodologies, and outputs to ensure they meet business and regulatory requirements.
• Risk Assessment:
• Identify model risks and limitations, and assess their potential impact on business decisions.
• Provide recommendations for mitigating identified risks and improving model accuracy and performance.
• Documentation and Reporting:
• Prepare detailed validation reports documenting the validation process, findings, and recommendations.
• Communicate validation results to model developers, risk managers, and senior management.
• Regulatory Compliance:
• Ensure models comply with relevant regulatory requirements and industry best practices.
• Stay updated on regulatory changes and their implications for model validation processes.
• Collaboration and Communication:
• Work closely with model developers to understand model design and implementation.
• Collaborate with risk management and other departments to integrate validation results into business processes.
• Continuous Improvement:
• Continuously improve validation methodologies and tools to enhance the efficiency and effectiveness of the validation process.
• Stay updated with the latest developments in model validation techniques and best practices.

Education and Experience:

• Bachelor’s degree in Mathematics, Statistics, Finance, Computer Science, or a related field.
• Proven experience in model validation, quantitative analysis, or a similar role.
• Strong understanding of statistical and mathematical modeling techniques.

Technical Skills:

• Proficiency in programming languages such as Python, R, or SAS.
• Experience with statistical and analytical tools and software.
• Knowledge of machine learning and artificial intelligence techniques is a plus.

Soft Skills:

• Excellent analytical and problem-solving skills.
• Strong verbal and written communication skills.
• Ability to work independently and as part of a team.
• Strong organizational skills and the ability to manage multiple tasks and priorities.

• Model Validation:
• Conduct comprehensive validation of models used for risk management, financial forecasting, pricing, and other business applications.
• Evaluate model assumptions, methodologies, and outputs to ensure they meet business and regulatory requirements.
• Risk Assessment:
• Identify model risks and limitations, and assess their potential impact on business decisions.
• Provide recommendations for mitigating identified risks and improving model accuracy and performance.
• Documentation and Reporting:
• Prepare detailed validation reports documenting the validation process, findings, and recommendations.
• Communicate validation results to model developers, risk managers, and senior management.
• Regulatory Compliance:
• Ensure models comply with relevant regulatory requirements and industry best practices.
• Stay updated on regulatory changes and their implications for model validation processes.
• Collaboration and Communication:
• Work closely with model developers to understand model design and implementation.
• Collaborate with risk management and other departments to integrate validation results into business processes.
• Continuous Improvement:
• Continuously improve validation methodologies and tools to enhance the efficiency and effectiveness of the validation process.
• Stay updated with the latest developments in model validation techniques and best practices