Senior Specialist, Loans Modeling & Analytics (CLO/CFO)

BNY Mellon•Houston, TX

1d•$59,000 - $88,000•Onsite

About The Position

BNY is seeking a Senior Specialist, Loans Modeling & Analytics to join its Corporate Trust Analytics Group, based in the Houston, Texas or Pittsburgh, Pennsylvania office. The role works across structured credit modeling, loans product management, technology, and analytics transformation. The specialist will help shape the future operating model for CLO and loans analytics by contributing to model and investor report development, modernization of the modeling platform, and adoption of agentic and AI-enabled capabilities throughout the workflow. The position supports CLO document review, data extraction, model development, quality control, analytics generation, and process automation. It combines analysis of complex transaction documentation with development and enhancement of models, reports, datasets, and scalable analytics processes. The role also collaborates with business, analytics, technology, operations, and data-provider teams, and mentors junior team members.

Requirements

Bachelor’s degree in Finance, Economics, Mathematics, Statistics, Financial Engineering, Data Science, Computer Science, or another highly quantitative discipline, or an equivalent combination of education and experience.
1–3 years of experience in the financial industry.
Strong interest in or knowledge of CLOs, loans, structured credit products, transaction types, and related concepts.
Experience building or supporting financial models, analytical tools, or data-driven workflows in a controlled business environment.
Proficiency in one or more programming or analytical languages or tools, such as Python, SQL, VBA, R, or similar technologies for workflow automation, model logic, data analysis, and quality control.
Advanced Excel skills and experience with analytics, workflow, or visualization platforms such as Power BI, Alteryx, SharePoint, or similar tools.
Ability to work with large and complex datasets, perform root-cause analysis, and translate data into business and analytical insight.
Strong problem-solving skills, intellectual curiosity, and attention to detail, including the ability to evaluate complex transaction structures and produce accurate, high-quality outputs.
Excellent written and verbal communication skills, including the ability to explain technical or structural concepts clearly to a range of stakeholders.
An innovation, modernization, and continuous-improvement mindset, with enthusiasm for transforming structured credit analytics through technology and AI-enabled solutions.

Nice To Haves

3–5 years of experience in financial modeling, structured finance, leveraged loans, CLOs, corporate trust analytics, data science, or related quantitative or analytical roles.

Responsibilities

Develop, maintain, quality-check, and enhance CLO compliance and waterfall models, including collateral quality tests, coverage tests, concentration limits, payment structures, and cash flow mechanics.
Analyze CLO indentures, offering memoranda, and related transaction documents, translating structural language into analytics requirements, modeling logic, and reporting outputs.
Build, review, and enhance investor reports, dashboards, and analytics covering compliance tests, noteholder distributions, asset-level information, and transaction metrics.
Apply quantitative modeling, data analysis, and scenario-based analysis to stress-test transactions and evaluate portfolio behavior, structural performance, and model outcomes.
Partner with internal teams and data providers to source, integrate, and validate datasets, maintaining data integrity across model inputs, calculations, and outputs.
Conduct reviews, reconciliations, and trend analyses to identify modeling issues, improve performance, strengthen controls, and enhance analytics processes and outputs.
Contribute to transformation of the CLO and loans modeling platform by helping define and implement scalable, efficient, and controlled solutions.
Support adoption of agentic and AI-enabled capabilities for document ingestion, clause analysis, data extraction, model setup and quality control, exception identification, and other analytical workflows.
Collaborate with business, analytics, technology, and operations teams on transaction requirements, process improvements, complex transaction challenges, modernization initiatives, and ad-hoc client requests.
Mentor junior team members and foster analytical rigor, innovation, accountability, and continuous learning.