Senior Data Scientist - AI Risk Consultant

Creative Solutions Services, LLC; Phoenix (AZ); On-site; USD 150,000 - 210,000; Full time

Job summary

Creative Solutions Services, LLC in Phoenix, AZ is seeking a Senior Data Scientist / Model Validation / AI Risk Consultant to independently validate fraud and entity resolution models within a regulated financial services context. You will challenge methodologies, document validation findings, and communicate risk and remediation to technical and business stakeholders.

Ideal candidates have hands-on experience validating fraud and entity resolution models, strong Python/SQL skills, and the

Qualifications

• Independent model validation in a regulated environment.
• Fraud model validation experience.
• Entity resolution validation experience.
• Provide concrete examples of prior validation projects including methodology, testing and remediation.

Responsibilities

• Perform end-to-end Fraud Model Validation including design, data quality, assumptions, performance and monitoring.
• Conduct Entity Resolution Validation evaluating matching logic, inputs and thresholds.
• Independently challenge modeling approaches and provide defensible validation conclusions and recommendations.
• Review model documentation, source data, feature engineering and implementation processes.
• Perform quantitative analyses using Python, SQL, or similar tools and communicate results.
• Develop validation reports communicating risks and remediation to stakeholders.
• Apply SR 11-7 / OCC 2011-12 and related risk frameworks.

Tools

Python

SQL

R

Job description

Senior Data Scientist / Model Validation / AI Risk Consultant

IMMEDIATE START - Location: MUST be local and able to work onsite in Phoenix, AZ
Work Authorization: U.S. Citizens or Green Card holders only (No third Parties or C2C )
Duration: Long term W2 Contract, 12 Months+

We are seeking an experienced Model Validation / AI Risk Consultant with a strong background in financial services, model risk management, and advanced analytics. This individual will be responsible for independently assessing complex fraud and entity resolution models, challenging methodologies, evaluating model performance, and documenting validation findings in alignment with established model risk standards.

Key Responsibilities

• Perform end-to-end Fraud Model Validation, including assessment of model design, methodology, data quality, assumptions, performance, limitations, and ongoing monitoring.
• Conduct Entity Resolution Validation, evaluating matching/linkage methodologies, identity resolution logic, data inputs, thresholds, false positives/negatives, and overall model effectiveness.
• Independently challenge model development approaches and provide clear, defensible validation conclusions and recommendations.
• Review model documentation, source data, feature engineering, testing results, controls, and implementation processes.
• Conduct quantitative analysis using tools such as Python, SQL, R, or similar technologies.
• Evaluate model performance, stability, bias, drift, benchmarking, and sensitivity where applicable.
• Develop comprehensive validation reports and clearly communicate findings, risks, and remediation recommendations to technical and business stakeholders.
• Apply model risk management principles and regulatory guidance such as SR 11-7 / OCC 2011-12 and related financial-services risk frameworks.

Required Experience

• Strong hands-on experience performing independent model validation within banking, financial services, fraud, AML, risk, or a highly regulated environment.
• Demonstrated experience specifically with Fraud Model Validation.
• Demonstrated experience with Entity Resolution / Entity Matching Model Validation.
• Ability to provide specific examples of prior validation projects, including:
  • Models or solutions validated
  • Validation methodology used
  • Testing and challenge techniques performed
  • Key issues or weaknesses identified
  • Recommendations or remediation provided
  • Lessons learned from previous engagements
• Strong understanding of model risk concepts including data quality, conceptual soundness, outcomes analysis, benchmarking, sensitivity testing, limitations, governance, and ongoing monitoring.
• Experience working with statistical, machine learning, AI, or analytical models.
• Strong Python/SQL and quantitative analytical capabilities preferred.
• Excellent written communication and ability to produce audit- and regulator-ready validation documentation.

Ideal Background

Candidates may come from Model Risk Management, AI/ML Model Validation, Fraud Analytics, Financial Crime Risk, Quantitative Risk, Data Science, or Regulatory Examination backgrounds. Experience validating models in large banks, financial institutions, consulting firms, or regulated enterprises is highly preferred.