Perform model monitoring activities for credit, customer, and non-customer decision models, including tracking of KPIs, stability metrics, and performance degradation indicators.
Create and maintain dashboards and reports that communicate performance trends, trigger alerts, and highlight potential model concerns.
Collaborate with model developers, owners, and validators to support timely issue investigation, remediation planning, and documentation updates.
Support the development and maintenance of monitoring frameworks, including stability thresholds, performance benchmarks, and early warning indicators.
Assist with the automation of recurring monitoring tasks using scripting (e.g., SAS, Python, SQL) and workflow tools.
Document model performance summaries, trend analyses, and key monitoring artifacts in accordance with model risk policies.
Prepare inputs for model risk reports, audit reviews, and regulatory requests, ensuring traceability and completeness of monitoring evidence.
Contribute to the adoption of MLOps best practices and explainability techniques (e.g., SHAP, LIME) to enhance monitoring transparency and trust.
Participate in cross-functional working sessions to evaluate monitoring outcomes and support continuous improvement initiatives.

Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 1+ years’ experience or in lieu of degree 3+ years of relevant work experience in model analytics, monitoring and validation or development within a financial services environment
Strong technical proficiency with data manipulation and analysis tools such as Python, SQL, R, or SAS.
Experience with data visualization tools like Tableau, Power BI, or similar platforms to create actionable performance dashboards.
Working knowledge of performance drift metrics, stability indicators, and key model health metrics.
Ability to translate technical findings into clear, concise documentation for non-technical audiences.
Experience with monitoring automation or process efficiency initiatives is a plus.
Ability to manage multiple models or monitoring streams independently, with a high attention to detail and quality.

best-in-class employee benefits and programs that cater to work-life integration and overall well-being
career advancement and upskilling opportunities

Analyst, Model Monitoring

Key skills