Fair Lending Analytics and Modeling Senior Associate (Flexible Hybrid)

Company Description

At Fannie Mae, futures are made. The inspiring work we do helps make a home a possibility for millions of homeowners and renters. 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 grow your career and help create access to fair, affordable housing finance.

Job Description

As a Senior Associate on the Fair Lending Oversight team, you will support Fannie Mae’s core mission of promoting fair lending. You will be part of a small impactful team of Fair Lending analytics professionals using statistical methods to conduct fair lending analysis on models, decision tools, products, policies, and initiatives.

We have one opening for this job and it can be worked on a Hybrid basis from one of our offices.

THE IMPACT YOU WILL MAKE
The Fair Lending Analytics and Modeling Senior 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:

• Assist team on fair lending risk assessments and fair lending compliance program reviews.
• Support the management of data, access, and systems to ensure historical and current analyses are preserved and accessible.
• Review traditional and artificial intelligence (AI) / machine learning (ML) models for fair housing and fair lending risks.
• Provide recommendations on modifications to statistical models that further support fair lending objectives.
• Design modeling applications that support fair lending risk identification, measurement, and mitigation.
• Gather and report on data necessary for fair lending assessments, focusing on data availability, and data quality.
• Apply best practices in research and fair lending testing to model, product, and policy development.
• Partner with team to design data visualizations, technical documentation, and nontechnical presentation materials to communicate ideas and solutions to lawyers, business partners, management, and regulators.

Qualifications

THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Required Experiences

• 2 years related experience.
• Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.
• Experience with Data Analytics and modeling including developing and testing hypotheses, using experimental design, linear and logistic regressions.
• Skilled in Python, R, SQL, and Excel.
• Familiarity with AI/ML explainability tools and building challenger models.
• Experience with the financial services industry with a focus in credit risk modeling or mortgages.
• Ability to work with people with different functional expertise respectfully and cooperatively towards a common goal.
• Excellent written and oral communication skills with ability to deliver complex technical information to audiences with various backgrounds.
• Skilled in presenting information and/or ideas to an audience in a way that is engaging and easy to understand using graphical representation of information in the form of a charts, diagrams, pictures, and dashboards.

Desired Experiences

• Experience in model validation, model risk oversight and/or model development.
• Master’s degree in Statistics, Data Science, Economics, or a related field (or comparable experience).
• 4 years of related work experience.
• Some knowledge of the use of statistical analysis related to anti-discrimination laws such as fair lending and housing.
• Familiarity with the Single Family and/or Multifamily mortgage business.
• Experience using BitBucket/GitHub.
• Experience with Tableau and R Markdown.
• Experience in AI/Machine Learning and Natural Language Models.
• Experience in AWS and machine learning tools, such as SageMaker.
• Skilled in applying econometric and statistical techniques including time series, panel data, discrete event modeling to mortgage performance modeling, property, and financial asset valuation modeling.
• Experience in the process of analyzing data to identify trends or relationships to inform conclusions about the data.
• Determining causes of operating errors in computer programs and taking corrective action.
• Familiarity with adversarial debiasing techniques.

Additional Information

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

Fannie Mae is a flexible hybrid company. We embrace flexibility for our employees to work where they choose, while also providing office space for in-person work if desired. At times, business need may call for on-site collaboration, which means proximity within a reasonable commute to your designated office location is preferred unless job is noted as open to remote.

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 [email protected].

The hiring range for this role is set forth on each of our job postings located on Fannie Mae's Career Site. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee’s physical, mental, emotional, and financial well-being. See more here.