Analytics & Modeling Program Associate – Early Career

Fannie Mae

Washington (District of Columbia)

Vor Ort

USD 105.000 - 125.000

Vollzeit

14 Tage+

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Zusammenfassung

Fannie Mae in Washington, DC is seeking an Analytics and Modeling Associate within the Enterprise Analytics program. It begins with a 10-week training on mortgage industry knowledge and quantitative analytics using SQL, R, and Python.

After training, you join an analytics-focused team to tackle business challenges with data-driven methods. You will apply advanced analytics, build self-service tools, and craft narratives to support risk reporting and decision making, with mentorship and growth

Qualifikationen

  • Bachelor's or Master's degree in a quantitative field, awarded between Dec 2026 and Spring 2027.
  • Authorization to work in the U.S. without sponsorship.
  • GPA 3.3 or higher preferred.
  • Experience with R, Python, and SQL.
  • Strong analytical background and leadership capabilities.
  • Excellent written and verbal communication.
  • Self-starter with business acumen and adaptability.

Aufgaben

  • Apply advanced analytics, machine learning, and econometric techniques to solve business problems.
  • Create self-service analytics tools for accessible insights.
  • Craft analytical narratives with data visualization.
  • Build models forecasting loan performance, property values, and market factors.
  • Conduct sensitivity and scenario analyses for financial and regulatory impact.

Kenntnisse

Analytical thinking
Leadership
Strong communication
Self-starter
Adaptability to new technologies

Ausbildung

Bachelor's or Master's degree

Tools

R
Python
SQL

Jobbeschreibung

Fannie Mae in Washington, DC is seeking an Analytics and Modeling Associate within the Enterprise Analytics program. It begins with a 10-week training on mortgage industry knowledge and quantitative analytics using SQL, R, and Python.

After training, you join an analytics-focused team to tackle business challenges with data-driven methods. You will apply advanced analytics, build self-service tools, and craft narratives to support risk reporting and decision making, with mentorship and growth

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