Analyst Responsible AI Quality

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Job Description

The Responsible AI Quality Analyst will ensure AI/ML solutions meet organizational and regulatory standards for fairness, transparency, accountability, and safety. This role is responsible for validating AI systems against Responsible AI (RAI) requirements throughout the model lifecycle, identifying risks and quality gaps, and enhancing compliance through structured testing and governance reporting. This position is critical to operationalizing Responsible AI within a highly regulated financial services environment. 

Essential Functions 

• RAI Test Strategy & Execution 

• Design and execute test plans, test cases, and validation scripts specific to RAI criteria (fairness, explainability, safety, privacy). 

• Perform structured validation of AI/ML models, including scenario-based testing and adversarial tests for bias and robustness. 

• Validate that models comply with Responsible AI policies, internal control frameworks, and applicable regulatory expectations (e.g., GDPR, SEC/FINRA, OCC). 

• Apply model monitoring tools and develop QA dashboards to track performance drift, concept drift, and fairness over time. 

• Cross-functional Collaboration 

• Partner with Data Science, Model Risk, Compliance, and Product teams to ensure integrated model quality and accountability. 

• Contribute to model documentation, test evidence packages, and audit-ready QA artifacts. 

• Support integration of Responsible AI checkpoints into SDLC, CI/CD, and MLOps pipelines. 

• Monitoring & Governance Reporting 

• Analyze post-deployment outcomes to detect deviations from expected model behavior. 

• Proactively flag performance degradations and coordinate recalibration or retraining efforts. 

• Provide detailed QA reporting to Responsible AI and Model Risk teams, including risk ratings and remediation plans. 

Qualifications 

• Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field. 

• 3+ years of experience in QA, model validation, or risk-based testing; 1+ year specifically with AI/ML model validation or assurance. 

• Working knowledge of bias detection, fairness metrics, interpretability frameworks (e.g., SHAP, LIME), and drift detection tools. 

• Experience testing AI models in cloud-native or hybrid environments (AWS preferred). 

• Familiarity with model documentation standards (e.g., Model Cards, Factsheets, Datasheets). 

• QA certifications (e.g., ISTQB) and/or coursework in AI ethics, RAI frameworks, or model risk management are a strong plus. 

• Excellent communication and documentation skills, with a strong focus on clarity and audit readiness. 

• The ideal candidate is a proactive self-starter with strong problem-solving skills and a forward-looking mindset. They anticipate future challenges and opportunities in AI, and bring a continuous improvement lens to model quality and Responsible AI practices. 

• Comfortable working across time zones and collaborating asynchronously with global teams. 

This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job.  The employer has the right to revise this job description at any time.   You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description.   You may be required perform other duties that are not included on this job description.  The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason.

We are an equal opportunity employer with a commitment to diversity.  All individuals, regardless of personal characteristics, are encouraged to apply.  All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.