MF Capital Markets - Financial Engineering - Lead Associate - REF6536V

Company Description

At Fannie Mae, futures are made. The inspiring work we do makes an affordable home a reality and a difference in the lives of Americans. Every day offers compelling opportunities to impact the future of the housing industry while being part of an inclusive team thriving in an energizing, flexible environment. Here, you will help lead our industry forward and make your career.

Job Description

As a valued colleague on our team, you will provide expert advice and guidance to the team responsible for applying mathematical models, advanced tools or techniques (such as SAS, Python, and R), and financial industry knowledge to business or financial data, including model results. Your efforts will enable the team to analyze or report on business performance, solve business questions, or inform business decisions. Work may include developing models or prototypes to achieve these goals, but is not the core focus in the role.

The MF Capital Markets - Financial Engineering - Lead Associate role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

  • Join and work with a team of several analysts to assess and monitor credit risk on Fannie Mae's $400bln + multifamily securitization book of business.
  • Learn and execute proprietary in-house forecasting and pricing models developed in java, Python and R, and analyzing the results. Analyze loan level results provided by off the shelf forecasting application, typically thru tools such as Excel Pivot Tables, R, Python
  • Understanding and assessing the upstream input data including MF loan data flows, transformations, and how changes to the upstream data drive changes in credit forecasts
  • Quantitatively analyze multifamily loan terms, products and securitizations through forecasts of NOI, Cap Rates, Interest Rates, Property Prices
  • Execute deterministic what-if scenarios thru proprietary tools to understand impact on MF loan book. Synthesize results and document methodology in brief memos using Monte Carlo and other simulation techniques
  • Implement code changes to modify and/or extend in-house models, or to develop new models from scratch
  • Understanding Multifamily loan securitizations and model their cash flows in Python and R. Perform discounted cash flow (NPV) analysis on forecasted loan structure cashflows
  • Understand, measure, communicate and document modeling assumptions, output transformations, and other modeling components drive the results of various analyses.
  • Participate with a team in developing, executing, validating, and documenting proprietary valuation models and property price indexes. Work collaboratively with stakeholders (business, finance, risk, economists) to discuss options and arrive at a recommended approach
  • Synthesize and share with management attribution and sensitivity analysis (attributing changes in model outputs to changes in inputs and assumptions, and understanding and documenting sensitivity of model outputs to changes in inputs and assumptions)
  • Perform what-if or strategic analysis to investigate how contemplated changes to loan terms might impact the financial outcomes (capital, returns, pricing) for Fannie Mae and the borrower



Minimum Required Experiences
  • 4 years

Desired Experiences
  • MBA with quantitative analytics experience, or Master's in Financial Engineering or Quantitative Analytics, or Ph.D. in Finance or Economics
  • 2 years experience developing and running financial models or analyzing large datasets (10mm+ observations) written in Python/Java/R. AWS experience preferred
  • 2 years experience communicating complex financial results to management with presentations or memos
  • Knowledge of SQL
  • 2 years experience developing and executing cashflow models/valuation/loss forecasting for loans or securitizations (such as CMBS, CRT)
  • Familiarity of GSE multifamily lending business, underwriting requirements, and GSE multifamily securitizations structured transactions

  • Experience gathering accurate information to explain concepts and answer critical questions
  • Determining causes of operating errors and taking corrective action
  • Communication including communicating in writing or verbally, copywriting, planning and distributing communication, etc.
  • Skilled in the graphical representation of information in the form of a charts, diagrams, pictures, and dashboards with programs and tools such as Excel, Tableau, or Power BI
  • Business Insight including advising, designing business models, interpreting customer and market insights, forecasting, benchmarking, etc.
  • Programming including coding, debugging, and using relevant programming languages
  • Expertise in using statistical methods, including: developing and testing hypotheses, using experimental design, and running linear and logistic regressions
  • Skilled in cloud technologies and cloud computing
  • Working with people with different functional expertise respectfully and cooperatively to work toward a common goal

  • Skilled in Tableau
  • Skilled in Excel
  • Skilled in SAS
  • Skilled in SQL
  • Skilled in using Bloomberg Professional
  • Skilled in Java
  • Skilled in Microsoft Teams
  • Skilled in Python object-oriented programming
  • Skilled in RStudio to develop programs in R
  • Skilled in using Intex
  • Experience using Macros in Excel
  • Skilled in Amazon Web Services (AWS) offerings, development, and networking platforms
  • Experience using JIRA

Additional Information

The future is what you make it to be. Discover compelling opportunities at

Fannie Mae is an Equal Opportunity Employer, which means we are committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, religion, national origin, gender, gender identity, sexual orientation, personal appearance, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation in the application process, email us at