Quantitative Analyst

Job Title: Quantitative Analyst

Position Type: Direct Placement (Full-time Permanent)

Location: Hybrid in Manhattan, NY, 10178

Attractive Base + Benefits + Bonus

Position overview

The Marketing Quantitative Research Analyst supports MAP (mission and product) strategy, refining loan eligibility standards and credit structure design through quantitative analysis of mortgage loan credit, performance and other characteristics. The role also performs model owner duties for credit models used by the department. The role may represent the business in enterprise technology, modelling and risk working groups and committees.

Essential job functions.

· Support Mortgage Credit Models and analysis used for loan eligibility.

· Support and upgrade mortgage credit models

· Document mortgage credit models

· Identify or develop benchmarking or challenger models.

· Respond to model-related requests and remediate findings from model validators, internal and external audit, and the regulator.

· Automate model integration with loan database in collaboration with I.T.

· Determine principal drivers of mortgage credit to include Home Price Index (HPI) to explain model results.

· Develop Research Capabilities to support Low Income and other Product Strategies

· Design large-scale data capabilities of public data to facilitate:

· Loan performance analysis of Fannie and Freddie single family loan dataset

· Loan Borrower Income characteristics from Federal HMDA loan data

· Mortgage loan Appraisal quality from FHFA dataset

· Home Price Appreciation from FHFA dataset

· Demographic information from Census data

Design analytical capabilities for business objectives:

· Research the characteristics and performance of loans to Low- and Moderate-Income borrowers to better serve that market

· Identify mortgage lending to underserved markets such as small originators, local markets, and concentrated demographics.

· Perform ad-hoc credit research for new mortgage sellers, emerging products, geography and underwriting characteristics.

· Research credit characteristics of potential new product classes

· Collaborate with the Data Management Office to explore data and analytical solutions.

· Provide Mortgage Market Surveillance for decision support.

· Develop prepayment and performance reports on mortgage loan cohorts.

· Automate analytics and surveillance report generation and publication.

· Benchmark AMA loan cohorts against GSE cohorts

· Collaborate with business and I.T. to create requirements for data and process enhancements to support the business.

· Develop data visualizations for business strategy, marketing, and sales management.

· Assist sales force by discussing loan credit quality with our client seller-servicers.

Skills & Experience

· 2+ years' experience performing a combination of statistical modelling, machine learning development, econometric analysis or financial modeling.

· Demonstrable experience supporting, benchmarking, back-testing, calibration, validation and development of statistical models.

· Application of statistical methods for predictive modeling such as: Monte-Carlo simulation, multivariate regression, generalized linear models, logistic regression, Poisson regression, AUC-ROC, principal component analysis, cross-validation, AIC, testing for normality, multicollinearity, and autocorrelation.

· Programming in Python or R with SQL for statistical analysis, aggregation, analysis and visualization of time series datasets. Experience optimizing queries and schemas for performance with large datasets (>1 billion rows).

· Familiarity with machine learning: clustering, decision trees and random forests are a plus.

· Basic mortgage finance and performance reporting, such as prepayment and credit performance analysis and statistical default-loss modeling a plus.

· Strong analytical, financial, interpersonal, verbal and written communication skills.

· Bachelor's degree in economics, statistics, quantitative finance, computer- or physical sciences or quantitatively related discipline or equivalent work experience.

· Chartered Financial Analyst (CFA) a plus.