Fair Lending Analytics Advisor

2 days ago

Plano, Texas, United States Fannie Mae Full time
Job Overview

As a key member of the Fair Lending Analytics and Modeling division, you will significantly influence the organization's strategic initiatives through insightful data analysis and recommendations. Your contributions will be vital in steering quantitative analytical projects and collaborating with various business units.

KEY RESPONSIBILITIES
The Fair Lending Analytics Advisor position provides you with the autonomy to shape your daily tasks while working with dedicated professionals. Your responsibilities will include:

  • Acting as a trusted consultant to senior management, delivering insights and recommendations derived from data analysis and predictive modeling.
  • Leading ongoing enhancement initiatives to improve analytical capabilities and broaden the application of analytics throughout the organization.
  • Assessing traditional and AI/machine learning models for potential algorithmic bias.
  • Conducting statistical analyses related to fair lending to identify and quantify associated risks.
  • Offering suggestions for adjustments to statistical models that align with fair lending goals.
  • Identifying organizational needs for analytical support, fair lending assessments, and quantitative evaluations.
  • Collecting and reporting on enterprise-wide data essential for fair lending assessments, data availability, and quality evaluations.
  • Reviewing policy modifications and analytical methodologies.
  • Extracting and analyzing data using relevant software while ensuring data integrity.
  • Effectively communicating complex information to both expert and non-expert audiences.
  • Evaluating new products and pricing model adjustments for fair lending implications.
  • Identifying any special monitoring requirements based on routine data evaluations.
  • Supporting the team in fair lending risk assessments and compliance program evaluations.
  • Implementing best practices in research and fair lending testing for model, product, and policy development.
  • Collaborating with the team to create data visualizations, technical documentation, and non-technical presentations to convey ideas and solutions to business partners, management, and regulatory bodies.

QUALIFICATIONS
Essential Experience

  • A minimum of 6 years in data analytics and reporting.
  • Proficiency in statistical methods and machine learning algorithms, including hypothesis development, experimental design, and executing linear and logistic regression models, along with other advanced techniques.
  • Expertise in programming, including coding, debugging, and validating using software such as R, Python, and SQL.
  • Experience in documentation and database reporting for analytical purposes, data discovery, and decision-making.
  • Proven ability to analyze data to uncover trends or relationships that inform conclusions.
  • Experience in gathering precise information to clarify concepts and address critical inquiries.
  • A collaborative approach to teamwork.
  • Capability in managing project plans, resources, and personnel to ensure successful project outcomes.
  • Exceptional interpersonal, written, and verbal communication skills.
  • Strong attention to detail and the ability to thrive in a fast-paced environment.
  • Experience in cross-functional collaboration with various business units.
  • Ability to streamline, validate, and test analytical processes for accuracy and consistency.

Preferred Experience

  • Master's degree or equivalent experience.
  • Background in Fair Lending analytics and reporting.
  • Prior experience in a financial institution or regulatory body.
  • Experience leading cross-functional initiatives with non-technical stakeholders such as legal professionals, compliance officers, and regulators.
  • Proficiency in MS Office Suite, including Excel, PowerPoint, and Word.
  • Experience with AWS SageMaker for building, tuning, and deploying machine learning solutions.
  • Familiarity with AWS Redshift data connections.

Additional Information
This position is classified as Hybrid, allowing for flexibility in work arrangements. Fannie Mae is committed to fostering a diverse and inclusive workplace, providing equal opportunity for all qualified applicants without regard to race, religion, national origin, gender, gender identity, sexual orientation, personal appearance, protected veteran status, disability, age, or other legally protected status.

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