Full-Time
Quantitative Model Validator Advisor
Flexible Hybrid
Confirmed live in the last 24 hours
Fannie Mae
10,001+ employees
Facilitates affordable housing through mortgage financing
Senior
Washington, DC, USA
Flexible hybrid role.
- 6 years of experience
- Bachelor's degree or equivalent
- An advanced degree (PhD. or Masters) in a quantitative field such as Statistics, Economics (with an Econometrics emphasis), Applied Finance, Engineering, or Computer Science.
- Experience with a large financial institution which has Enterprise Risk Management functions that meet the needs of highly regulated financial institutions.
- Experience in developing models or validating models.
- Experience with Large Language Models and Generative AI.
- Familiarity with the broader technology landscape, including emerging trends in AI and Data Science.
- Understanding the business context which may create a need for models or other analytical product solutions.
- Fast-learning, building on a strong foundation of knowledge to continuously learn new techniques for building and managing model risks well.
- Ability to communicate technical subject matters clearly and concisely, both verbally and through well-written communications including Validation Reports.
- Advanced skills in using computer languages often used in model development such as Python and R.
- Advanced skills in machine learning libraries such as TensorFlow, PyTorch, or Scikit-Learn.
- Nice to have: skills in Hugging Face Transformers and related technology ecosystem.
- Advanced skills in using computer languages that facilitate producing technical documents about models, those with equation editors and convenient ways of producing charts and tables which describe models and summarize model diagnostics.
- Recommend improved methods and techniques to provide innovative, thorough, and practical solutions that support business strategies and initiatives, as well as better ways of conducting or assessing 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.
- Counsel teams on company policies and industry-wide modeling practices.
- Inform the team's technical direction for validation or testing strategies and assessment of quality and risk of model methodologies, outputs, and processes and applying understanding of relevant business context to interpret model results, monitor performance, and assess risks.
- Communicate technical subject matter clearly and concisely to team leadership and project stakeholders.
Fannie Mae operates in the U.S. housing finance market, focusing on making housing more affordable for homeowners, homebuyers, and renters. The company achieves this by purchasing mortgages from lenders, which provides these lenders with the cash flow needed to offer more loans. Fannie Mae's business model includes holding some of these mortgages in its portfolio and packaging others into mortgage-backed securities (MBS) that are sold to investors. This process helps spread risk and ensures a steady flow of capital into the housing market, promoting homeownership and rental opportunities. Fannie Mae generates revenue through fees for guaranteeing MBS payments and from interest on its mortgage portfolio. The company is committed to community service and workplace diversity, earning recognition for its inclusive practices and positive work environment.
Company Stage
IPO
Total Funding
N/A
Headquarters
Washington, District of Columbia
Founded
N/A
Simplify's Take
What believers are saying
- Fannie Mae's strategic initiatives, such as the MH Advantage program, offer new affordable housing options, potentially expanding their market reach.
- The company's robust issuance program, like the $659 million Connecticut Avenue Securities deal, demonstrates its strong position in the credit risk-sharing market.
- Recognition for corporate responsibility and impact, as highlighted in their 2023 CRI Report, enhances Fannie Mae's reputation and stakeholder trust.
What critics are saying
- The ongoing affordability constraints in the housing market could limit the number of buyers, impacting Fannie Mae's business volume.
- Economic uncertainties, such as potential GDP growth downgrades and inflation volatility, could affect the housing market and Fannie Mae's financial performance.
What makes Fannie Mae unique
- Fannie Mae's role as a government-sponsored enterprise uniquely positions it to provide liquidity and stability in the U.S. housing market, unlike private sector competitors.
- Their ability to package purchased mortgages into mortgage-backed securities (MBS) and sell them to investors spreads risk and ensures a steady flow of capital back into the housing market.
- Fannie Mae's commitment to community service, diversity, and inclusion, as evidenced by numerous accolades, sets it apart in the financial services sector.
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