Goldman Sachs
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.