Financial Data Engineer Senior Associate (Hybrid)

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Join Fannie Mae: A Future of Opportunities

Company Description:

At Fannie Mae, futures are made. Our inspiring work helps make homes a reality for millions of homeowners and renters. Every day, you will find compelling opportunities to impact the future of the housing industry while being part of an inclusive team within an energizing, flexible environment. Here, you will grow your career and help create access to fair, affordable housing finance.

Job Description:

As a valued colleague on our team, you will support the team by applying mathematical models, advanced tools (such as SAS, Python, and R), and financial industry knowledge to business or financial data, including model results. Your role will enable the team to analyze or report on business performance, solve critical business questions, and inform key business decisions. While you may develop models or prototypes to achieve these goals, this is not the core focus of the role.

The Impact You Will Make:

The Financial Data Engineer Senior Associate (Hybrid) role offers you the flexibility to make each day your own, collaborating with people who care to deliver on the following responsibilities:

  • Collaborate on processing or analyzing large data efficiently using advanced financial engineering tools and techniques.
  • Determine customer's intended uses for a financial analysis or model.
  • Conduct financial analysis or forecasting, including scenario or sensitivity analysis, stress testing, or attribution analysis.
  • Execute models and interpret model results, translating analysis or model results into understandable conclusions for the customer.
  • Work directly with model builders to vet new models, suggest changes to existing models, or analyze model performance data.
  • Perform data and systems analysis, validation, and regression testing.

The Experience You Bring to the Team:

Minimum Required Experiences:

  • 2 years of relevant experience.

Skills:

  • Experience gathering accurate information to explain concepts and answer critical questions.
  • Ability to work respectfully and cooperatively with people of different functional expertise to achieve a common goal.
  • Operational Excellence, including improving and overseeing operations.
  • Proficiency in representing information graphically using tools such as Excel, Tableau, or Power BI.
  • Programming skills, including coding, debugging, and using relevant programming languages.
  • Risk Assessment and Management, including evaluating and designing controls, conducting impact assessments, identifying control gaps, and remediating risk.
  • Expertise in using statistical methods, including developing and testing hypotheses, using experimental design, and running linear and logistic regressions.
  • Skills in identifying and correcting operating errors.
  • Presenting information and/or ideas to an audience engagingly and understandably.
  • Communication skills, both written and verbal, including copywriting and planning and distributing communication.
  • Business Insight, including advising, designing business models, interpreting customer and market insights, forecasting, and benchmarking.
  • Ability to approach problems as systems and analyze inputs, outputs, and processes.

Tools:

  • Skilled in SAS.
  • Proficient in SQL.
  • Experience using SharePoint.
  • Proficient in Tableau.
  • Skilled in Excel.
  • Experience with Amazon Web Services (AWS) offerings, development, and networking platforms.
  • Proficient in Microsoft Teams.
  • Skilled in R Language Programming.
  • Experienced in Python object-oriented programming.

Desired Experiences:

  • Educational background or work experience in economics, finance, and/or statistics preferred.
  • CFA designation or progress towards obtaining it is a plus.
  • In-depth knowledge of the mortgage market from origination to loss mitigation, including capital markets; multifamily or commercial real estate experience preferred.
  • Independent thinker and intellectually curious.
  • Experienced in using computer programming applications such as Python, R, SAS, SQL, and other statistical software.
  • Familiarity with Tableau, Power BI, or other business intelligence tools.
  • Familiarity with relational databases and SDLC.
  • Demonstrated experience engaging with stakeholders to design and develop reports and other analytical tools for data-driven decision-making.
  • Experience in forecasting, stress testing, and/or capital analysis is preferred.