Senior ALM & IRRBB Quant Analytics

Fairygodboss; Charlotte (NC); On-site; USD 123,000 - 296,000; Full time

Benefits offered by this job

401(k) with PNC match

Medical/dental/vision benefits

Educational assistance

Job summary

PNC is seeking a Quantitative Analytics and Model Expert to provide second-line oversight of IRRBB, focusing on NII/EVE frameworks, with opportunities to collaborate across functions and contribute to CCAR processes.

The role requires strong quantitative skills, proficiency in Python and SQL, and the ability to engage with Front Office, Finance, IT, Legal, and Compliance. Location options include multiple cities with in-office expectations.

Qualifications

• 5+ years of experience in IRRBB, Market Risk, ALM, or Treasury.
• Strong knowledge of NII and EVE frameworks.
• Proficiency in Python and SQL; familiarity with QRM, Aladdin, PolyPaths, and Murex is a plus.
• Bachelor's or Master's degree in Finance, Economics, or quantitative fields.

Responsibilities

• Support the Head of IRRBB in executing risk oversight strategy.
• Develop analytics and automation using Python and SQL.
• Monitor IRRBB exposures and validate adherence to limits.
• Quantify and analyze risks including deposit modeling, rate models, OAS, and mortgage portfolios.
• Partner with Front Office, Finance, IT, Legal, Compliance, and other stakeholders.
• Contribute to CCAR processes, regulatory reviews, and governance forums.

Skills

Python

SQL

IRRBB

NII & EVE

Communication

Education

Bachelor's or Master's degree in Finance/Economics/quantitative fields

Tools

QRM

Aladdin

PolyPaths

Murex

Job description

PNC is seeking a Quantitative Analytics and Model Expert to provide second-line oversight of IRRBB, focusing on NII/EVE frameworks, with opportunities to collaborate across functions and contribute to CCAR processes.

The role requires strong quantitative skills, proficiency in Python and SQL, and the ability to engage with Front Office, Finance, IT, Legal, and Compliance. Location options include multiple cities with in-office expectations.