Senior Analytics & Modeling Associate

Fannie Mae•Reston, DC

8d•Hybrid

About The Position

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home. As a valued colleague on our team, you will, under limited supervision, conduct theoretical and empirical research with public and proprietary data in all areas of mortgage finance business, including mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models including housing prices and interest rate, financial valuation of finance assets and derivatives, economic capital, and stress testing.

Requirements

2 years experience performing quantitative analysis, statistical modeling, or predictive analytics to solve complex business problems
Experience using programming languages such as Python, SAS, R, or SQL for data analysis, model development, and automation
Experience working with large, structured and unstructured datasets, including data preparation, validation, and quality assessment
Experience communicating analytical findings and technical concepts to both technical and non-technical stakeholders through clear documentation and presentations
Experience collaborating with cross-functional teams, including business, technology, risk, and governance partners, to deliver analytical solutions
Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work

Nice To Haves

Bachelor degree or equivalent
Experience in financial services, mortgage finance, banking, or risk management
Knowledge of statistical and machine learning techniques, such as regression, classification, clustering, time series forecasting, or tree-based models
Experience with cloud-based analytics platforms (AWS, Azure, or GCP), Git, and data visualization tools such as Tableau or Power BI

Responsibilities

Apply moderately complex mathematical, statistical, and econometric techniques to provide innovative, thorough, and practical solutions that support business strategies and initiatives.
Conduct or assess ad-hoc quantitative analyses, modeling, or programming using SAS, SQL, R, or Python.
Utilize advanced data mining and/or statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations.
Identify opportunities to apply quantitative methods to improve business performance.
Apply experience and skill to complete modeling projects aligned with established company policies and industry-wide modeling practices.
Implement validation or testing strategies and assess the quality and risk of model methodologies, outputs, and processes.
Apply understanding of relevant business context to interpret model results, monitor performance, and assess risks.
Communicate complex technical subject matter clearly and concisely, both verbally and through written communication, such as white papers, review reports, or workpapers.