AI & ML

The Senior Responsible AI Analyst ensures that AI/ML systems are developed, deployed, and operated in ways that are trustworthy, compliant, and aligned to company values and customer expectations. The role blends technical evaluation of model behavior with governance, risk analysis, and cross-functional coordination to reduce harm, improve transparency, and strengthen accountability across the AI lifecycle.

The **Senior Model Risk Analyst** is a senior individual contributor in the AI & ML organization responsible for identifying, assessing, challenging, and monitoring risks introduced by statistical models, machine learning (ML) systems, and increasingly **GenAI/LLM-enabled** capabilities across the model lifecycle. The role ensures that models used in products and internal decisioning are **fit-for-purpose, reliable, explainable where required, secure, fair, and compliant** with applicable policies, contractual commitments, and emerging AI regulations.

The Responsible AI Analyst ensures that AI/ML systems are designed, evaluated, deployed, and monitored in ways that are fair, reliable, safe, privacy-preserving, transparent, and aligned with company policies and applicable regulations. This role translates Responsible AI principles into concrete assessments, evidence, documentation, and risk controls that product and engineering teams can execute without slowing delivery unnecessarily.

The **Principal Responsible AI Analyst** is a senior individual-contributor role that designs, operationalizes, and continuously improves the company’s Responsible AI (RAI) measurement, assurance, and governance practices across AI/ML-enabled products and internal AI platforms. The role blends rigorous analytical capability (risk quantification, model evaluation, monitoring) with enterprise operating-model strength (controls, evidence, decision gates, and stakeholder alignment) to ensure AI systems are trustworthy, compliant, and fit-for-purpose.

The Principal Model Risk Analyst is a senior individual contributor responsible for identifying, assessing, mitigating, and continuously monitoring risks arising from machine learning (ML) and generative AI models used in software products and internal decision systems. The role ensures that models are fit-for-purpose, robust, secure, compliant with emerging AI regulations and internal policies, and operationally reliable across their lifecycle—from experimentation through production and post-deployment monitoring.

The Model Risk Analyst identifies, measures, monitors, and helps mitigate risks arising from AI/ML models used in software products and internal decision systems. The role evaluates model design and usage against expected performance, reliability, security, privacy, fairness, and governance standards, and ensures model risk controls are proportionate to impact and exposure.

The Lead Responsible AI Analyst ensures that AI/ML systems—including generative AI features—are designed, evaluated, and operated in ways that are safe, fair, transparent, privacy-preserving, and compliant with evolving regulations and internal policies. This role blends rigorous analytics (measurement, evaluation, monitoring) with governance execution (risk assessments, controls, evidence, sign-offs) to help teams ship AI responsibly without slowing delivery unnecessarily.

The **Lead Model Risk Analyst** is a senior individual contributor who designs, runs, and continuously improves the organization’s **model risk management (MRM)** capability for machine learning (ML) and AI systems—ensuring models are safe, reliable, compliant, and fit-for-purpose before and after release. The role combines analytical rigor (validation, testing, metrics, monitoring) with governance leadership (risk taxonomy, controls, approvals, and audit readiness) in a fast-moving software/IT environment where AI is embedded in products and internal platforms.

The **Junior Responsible AI Analyst** supports the organization’s ability to design, evaluate, and operate AI systems that are **fair, reliable, safe, privacy-preserving, transparent, and accountable**. The role focuses on **evidence generation** (analysis, testing, documentation, and monitoring) to help product and engineering teams identify and reduce AI risks before and after deployment.

The **Junior Model Risk Analyst** supports the safe, reliable, and compliant use of machine learning (ML) and statistical models by helping evaluate model risk across the lifecycle—from design and development through deployment and monitoring. The role focuses on executing defined model risk management (MRM) activities (testing, documentation review, control evidence, monitoring checks) under the guidance of more senior model risk, responsible AI, or governance leads.

The **Associate Responsible AI Analyst** helps ensure that AI-enabled products and internal ML systems are designed, evaluated, documented, and monitored in ways that are **fair, reliable, safe, privacy-preserving, secure, transparent, and accountable**. The role supports Responsible AI (RAI) governance by performing structured assessments, maintaining evidence artifacts, executing repeatable evaluation workflows, and partnering with engineering and product teams to reduce user and business risk.

The **Associate Model Risk Analyst** supports the identification, assessment, documentation, and ongoing monitoring of risks arising from machine learning (ML) and AI models used in software products and internal systems. The role focuses on **model risk governance execution**—helping ensure models are trustworthy, explainable where needed, compliant with applicable policies and regulations, and appropriately controlled across their lifecycle.