Citi Group Data Science Sr Lead Analyst SVP - Fair Lending Mortgage Analysis 

United States, District of Columbia, Washington 

165599075

Serves as a key member of the Fair Lending Analytics and Monitoring ICRM team, which has responsibility for all data management, metrics and statistical analysis for the enterprise-wide fair lending compliance across Citi’s US businesses. The Data Science Senior Lead Analyst will be required to conduct statistical analyses related to mortgages for both Retail and Wealth channels, and when needed – also to support Cards and Small Business projects, focusing on fair lending aspect in order to identify and measure Citi’s exposure to fair lending risk. The position requires strong quantitative background, excellent communication and presentation skills, compliance risk management attitude, critical thinking, and experience in data validation and methodology documentation – both technical and non-technical.

Responsibilities

• Design and employ statistical analysis and modeling techniques to assist Fair Lending Analytics and Monitoring and all relevant business units in their compliance with Citigroup Fair Lending Policy and all Fair Lending laws and regulations.
• Document methodology and execution of analyses according to the established approached, following existing templates and practices.
• Lead enhancements of the existing in-house fair lending analytical methodologies and practices used to identify fair lending risks through the entire mortgage lifecycle, including underwriting, pricing, and loss mitigation. Identified enhancements should be sufficiently practical for implementation for projects for other lines of business.
• Where applicable seek improvements in implemented processes and support other team members in data mining, data assessment, validation, analysis, and correction to determine any limitations on reliability or usability.
• Provide active support (including presentation) during the exams and audits, and executive communication to top management.
• Support management during the work with examiners and business units to resolve any questions related to analytical methodology or data integrity.
• Support management in advising the business units, regulatory examiners, and other interested parties on quantitative methods and analysis, and presenting results in the form of articles, reports, or presentations.
• Develop and deepen Subject Matter Expertise in large Fair Lending, and HMDA as well as in specific fair lending analytics field through internal, external and on-the-job training.
• Act as a quality reviewer for work conducted by other team members.
• Special projects assigned at the direction of the direct manager.
• Coaching and mentoring others when applicable.
• Additional duties as needed.
• This is an individual contributor position.

Qualifications

• Direct experience in fair lending and analytics strongly preferred. Hands-on experience with analysis using HMDA data and experience in analytics related to mortgages and housing market strongly preferred.
• Expertise and hands-on experience in advance programming using: SAS / R / Python, and SQL for basic data mining; additional experience and knowledge of Big Data tools preferred.
• In-depth knowledge and understanding, and demonstrated experience working with logistic regression model development, univariate and multivariable statistics, sampling designs, disparities analysis.
• Ability of outside-of-box thinking and presenting complex ideas in a simple manner.
• Excellent communication skills (oral and written in English). Must be a team player and able to support team deliverables while delivering on individual responsibilities.
• Strong ability to work both collaboratively and independently. Knowledge of consumer lending products and regulatory requirements including ECOA and FHA preferred.
• Fair Lending knowledge and experience highly preferred.
• HMDA data and mortgage experience highly preferred.
• Project management, overseeing others’ work, coaching experience highly preferred.
• Executive presentations experience highly preferred.

Education

• Bachelor’s degree or 12+ years equivalent experience in a highly quantitative field, such as data science, applied economics, applied statistics, mathematics, or physics.
• 10+ years experience in a highly quantitative field, such as data science, applied economics, applied statistics, mathematics, or physics and Master’s degree preferred.
• 5+ years experience in a highly quantitative field, such as data science, applied economics, applied statistics, mathematics, or physics and Ph.D. preferred.

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