Specialist, Loans Modeling and Analytics -Structured Debt/CLO

BNY; Pittsburgh (Allegheny County); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

401(k) plan

Medical, dental, and vision insurance

Paid time off

Job summary

BNY is seeking a Specialist in Loans Modeling and Analytics to work in Pittsburgh, PA or Houston, TX. In this role, you will employ your quantitative expertise in debt markets to enhance CLO compliance and waterfall models while analyzing complex legal documents and investor reports.

The ideal candidate should possess a Bachelor’s degree in a quantitative field and have 2-3 years of relevant experience in financial data analysis and structured finance. Additional skills in programming and analytics tools like Excel and Power BI are also essential.

Qualifications

• 2‑3 years of experience in financial data analysis and structured finance.
• Basic understanding of CLO products and transaction types.
• Strong analytical and problem-solving skills.

Responsibilities

• Develop, maintain, and enhance CLO compliance and waterfall models.
• Analyze complex legal documents related to CLOs.
• Build and analyze investor reports for compliance tests.

Skills

Financial data analysis

Quantitative modeling

Communication skills

Analytical mindset

Programming (VBA, Python, R, SQL)

Education

Bachelor’s degree in Finance or related field

Tools

MS Excel

Power BI

Alteryx

SharePoint

Job description

Job Description

Specialist, Loans Modeling and Analytics (Structured Debt/CLO). In this critical role, you will leverage your expertise in debt markets and quantitative modeling to drive accuracy, efficiency, and actionable insights across model and investor report development for CLO and loan products. This role is located in our Houston, TX or Pittsburgh, PA office.

Responsibilities

• Develop, maintain, QC, and enhance CLO compliance and waterfall models, including detailed analysis of coverage tests, collateral quality tests, concentration limits, payment structures, and cash flow mechanics to ensure adherence to indenture provisions.
• Analyze and interpret complex legal documents such as CLO indentures, offering memoranda, and related transaction documents, providing comments around modeling and analytical matters.
• Build and analyze investor reports and dashboards that detail compliance tests, noteholder distributions, asset-level information, and other key metrics, enabling timely and transparent communication with stakeholders.
• Utilize quantitative modeling techniques and predictive analytics to calculate and assess CLO portfolio performance, risk exposures, and stress test under various scenarios.
• Work with internal teams, client reference data, and other external data providers to integrate and validate datasets, ensuring high data integrity for model inputs and outputs.
• Perform statistical and trend analyses to identify model discrepancies, optimize performance, and implement enhancements to address issues in alignment with evolving market conditions and transaction structures.
• Collaborate with cross‑functional teams to align on transaction requirements and support ad hoc reporting and analytics requests.
• Champion continuous improvement and data‑driven innovation by identifying opportunities for automation and efficiency and supporting strategic initiatives aimed at enhancing team capabilities.

Qualifications

• Bachelor’s degree in Finance, Economics, Mathematics, Financial Engineering, Data Science, Computer Science, or related quantitative discipline or the equivalent combination of education and experience.
• 2‑3 years of experience in financial data analysis, structured finance, corporate trust, CLOs, leveraged loans, or related products with a strong focus on quantitative modeling and analytics.
• Basic understanding of CLO products and transaction types such as new issue, refinancings, and resets and familiarity with related concepts.
• Beginner proficiency in programming languages such as VBA, Python, R, and/or SQL for coding payment and compliance rules, automating workflows, and building robust analytical tools with a strong desire for further development.
• Experience in quantitative finance and technology preferred with advanced skills in MS Excel (including macros, advanced functions, and data manipulation), SharePoint, Alteryx, Power BI, or other platforms to develop dynamic reports, analytics, and visualizations.
• Strong analytical mindset and problem‑solving skills with demonstrated ability to apply quantitative techniques and predictive analytics to structured credit products.
• Strategic thinker with excellent communication skills and the ability to translate complex concepts into clear insights for diverse audiences.
• Maintain a high level of accuracy and attention to detail to ensure the integrity of financial models and reports.

Compensation and Benefits

Base salary offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Base salary is only part of the total rewards package, which may include eligibility for an annual discretionary incentive award. Eligible employees may enroll in a 401(k) plan, and participate in company‑sponsored medical, dental, vision, and basic life insurance plans for the employee and the employee’s eligible dependents. Eligible employees also may receive other benefits such as various paid time off benefits, including vacation and sick time, dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

At‑will employment: The Company reserves the right to modify base salary (as well as any other discretionary payments or compensation programs) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Equal Employment Opportunity

BNY is an Equal Employment Opportunity/Affirmative Action Employer – Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.