Business Information Management Analyst II

Our client, is seeking a high-performing Business Information Management Analyst II (Data Scientist II – Model Health & Governance) to join their Model Health Center of Excellence (CoE). In this critical analytical and governance role, you will represent the First Line of Defense for assigned production models, ensuring they remain compliant, effective, monitored, and sustainable throughout their lifecycle.

Combining data science capabilities, quantitative analytics, and model risk governance, you will execute ongoing performance monitoring across a portfolio of production models utilizing Python, SQL, Databricks, and PySpark. Working as a primary liaison between Business Owners, Model Vendors, Model Validation (MV), Compliance, and Risk partners, you will investigate performance anomalies, author audit-ready Model Development Reports (MDRs), and support regulatory reviews within a highly regulated banking environment.

Duration: 6-Month Contract (with potential for extension) Advantages High-Impact Governance Scope: Serve as a core First Line representative driving model health, compliance, and performance oversight for critical enterprise models. Modern Big Data Stack: Leverage Databricks, PySpark, Python, and SQL to extract, transform, and analyze large-scale datasets. Cross-Functional Executive Exposure: Collaborate directly with senior business leaders, third-party model vendors, Model Validation teams, Compliance, and Regulatory partners.

Continuous Process Innovation: Drive automation, process efficiencies, and emerging AI governance standards across enterprise analytics frameworks. Responsibilities Model Performance Monitoring & Analytics Performance Monitoring: Execute ongoing monitoring routines across production models using Python, SQL, Databricks, and PySpark to evaluate stability, usage, data quality, and key risk metrics.

Anomaly & Risk Investigation: Investigate model performance issues, threshold breaches, data anomalies, and emerging risks; perform quantitative trend analysis to support governance decisions. Executive Dashboards: Develop clear monitoring reports, performance dashboards, and executive-ready presentations for internal stakeholders and risk committees. Model Governance, Validation & Vendor Management Lifecycle Governance Support: Support model onboarding, annual model reviews, ongoing validation cycles, and model remediation initiatives.

Audit-Ready Documentation: Prepare and maintain comprehensive governance documentation, including Model Development Reports (MDRs), Monitoring Plans, validation responses, and control evidence. Stakeholder & Vendor Liaison: Serve as a key liaison between Business Owners, Model Vendors, Model Validation, Compliance, and Technology teams; review and challenge vendor-provided model documentation and performance reports.

Regulatory Compliance: Coordinate cross-functional responses to Model Validation, Internal Audit, and Regulatory inquiries. Qualifications Professional Analytics Experience: 2+ years of professional experience in data science, quantitative analytics, model governance, model risk management, fraud analytics, or financial crime analytics. Programming & Big Data Depth: Strong hands-on programming proficiency in Python and SQL, paired with direct experience working in Databricks and PySpark environments.

Machine Learning & AI Methodologies: Strong quantitative understanding of machine learning and AI model methodologies (e.g., supervised/unsupervised learning, classification, regression, ensemble methods, and anomaly detection). Communication & Documentation: Excellent documentation, presentation, and verbal communication skills; proven ability to translate complex technical model concepts for non-technical business partners.

Preferred Assets & Nice-to-Haves Direct experience working with Model Validation, Compliance, Audit, Model Risk Management (MRM), or Regulatory partners. Experience evaluating and reviewing third-party vendor models. Prior experienc