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Global Banking & Markets - Private - Structured Finance Trade Analytics - Analyst

Dallas, TX, United States

Pay
Pay not listedSimilar roles state $94K–$143K
Work setting
Not stated
Employment
Not stated
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What you’ll work on

Full posting
  • Manipulate loan-level data across millions of records to build portfolio insights

  • Build portfolio stratifications and replines, and validate the underlying data

  • Run collateral analysis and asset pool selection across the full deal lifecycle

  • Model CPR speeds, loss severity and credit enhancement from rating agency models

  • Build historical performance matrices and work with rating agencies on projections

From the employer’s posting
Perform large-scale data manipulations across millions of loan-level records
Perform data validations and create portfolio level stratification and replines.
Own portfolio collateral analysis across full deal lifecycle
Provide pool level CPR speeds, loss severity and credit enhancement from RA (Fitch, KBRA, Moodys, Milan) models.
Work with rating agencies and create historical performance matrices (CPR, CDR, Charge off, Recoveries, Loss) to project future performance.
Education & alternatives
MINIMUM EDUCATION REQUIREMENTS/DEGREE AND FIELD: Bachelor’s degree (U.S. or foreign equivalent) MINIMUM YEARS EXPERIENCE REQUIRED:

Tools in this posting

  • Python
  • SQL
Source — Tool mentions in context
- Perform data validations and create portfolio level stratification and replines. - Own portfolio collateral analysis across full deal lifecycle – from asset selection, pricing, marketing and closing using python, CAS, and SQL. - Provide pool level CPR speeds, loss severity and credit enhancement from RA (Fitch, KBRA, Moodys, Milan) models.
- Undergraduate in Finance, Economics, Mathematics, or other STEM related degrees. - Experience with python, SQL and reporting tools required. - Experience working with large structured and unstructured datasets (millions/ billions of loan records).

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Oct 29, 2026 · today
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Employer says posted
Oct 9, 2026

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Job description

View original posting ↗

The Structured Finance Analytics team under Global Banking & Markets division is seeking a motivated professional to support the Credit & Asset Finance business. The team has product expertise across residential assets, consumer loans, real estate, and warehouse financing. The position sits at the core of securitization execution. A successful candidate will architect optimization frameworks and demonstrate an affinity for a solution-oriented mindset. The successful candidate will be responsible for the following: 

JOB DUTIES:

  • Perform large-scale data manipulations across millions of loan-level records delivering portfolio-level insights and strategic asset selection to traders, bankers and clients using statistical methods.
  • Act as a client advisor and perform analytics on all advisory securitization transactions including any MBS classes and consumer ABS classes. Responsibilities include: 
    • Collaborate with clients and work with data from various sources including: 
      • Settlement Data
      • Latest Month End Servicer Data
      • TPR due diligence Data 
      • Originator Data 
    • Perform data validations and create portfolio level stratification and replines. 
    • Own portfolio collateral analysis across full deal lifecycle – from asset selection, pricing, marketing and closing using python, CAS, and SQL.
    • Provide pool level CPR speeds, loss severity and credit enhancement from RA (Fitch, KBRA, Moodys, Milan) models. 
    • Assist in populate credit memo and PPM materials with outside accountants and lawyers.
    • Perform asset pool selection based on contribution requirements on ABS/CMBS securitization. 
  • Work with rating agencies and create historical performance matrices (CPR, CDR, Charge off, Recoveries, Loss) to project future performance. 
  • Manage cross-functional relationship with the desk, IBD, transaction management, diligence, operation, controller, and technology team to ensure monthly portfolio activities are accurately represented.
  • Strong communication skills (written and spoken) to translate technical analytics into client-facing insights. 

 

MINIMUM EDUCATION REQUIREMENTS/DEGREE AND FIELD:

Bachelor’s degree (U.S. or foreign equivalent) 

MINIMUM YEARS EXPERIENCE REQUIRED:

0 to 3 years of loans / Fixed income experience or internship in related fields 

Preferred Skillsets: 

  • Undergraduate in Finance, Economics, Mathematics, or other STEM related degrees.
  • Experience with python, SQL and reporting tools required.
  • Experience working with large structured and unstructured datasets (millions/ billions of loan records).
  • Understanding of fixed income analytics (duration, convexity, yield modeling).
  • Familiarity with mortgage or consumer credit performance data.
  • Ability to operate in high-pressure execution environment with parallel deal flow.
Source details

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Location & working pattern

Dallas, TX, United States

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