Quantitative Analytics Manager

• May 2021 - Present

Data Science Senior Manager

• Sep 2017 - May 2021

• Leading the Wholesale Risk Analytics team responsible for developing credit risk models for the Wholesale portfolio.• Working with multi-disciplinary teams in developing hybrid models to combine the subject matter expertise with statistical methods effectively.• Development of models for low-default portfolios using machine learning methods and internal data, reducing the number of overrides by 30%.• Managing the strategy to ensure a data-driven philosophy in Risk. Laying out the training plan for data scientists and definition of innovative use cases to achieve this goal. • Streamline the current Economic Capital process to leverage the Credit Risk Parameters (PD, LGD) coming from CECL/IFRS9. Aiming to reduce the time devoted to calculate the Economic Capital by 50%.• Responsible for reporting the retail and commercial portfolio models’ performance to the management committee to identify model needs and new re-developments.• Put in place an Early Warning System to identify high-risk industries given the lack of updated financial information during the COVID19 crisis based on macroeconomic and market signals.• Supervising the implementation of the models in the new platform using Provenir Show less

Data Scientist

• Oct 2012 - Sep 2017

• Conducted gap analysis regarding monitoring practices for credit risk models and their interdependent models (e.g. econometric, loan volume, loss forecasting) to remain CCAR compliant. • Maintained compliance with the Federal Reserve Board and recognized for exceeding the minimum applicable regulatory requirements set by the Dodd-Frank Stress Act Stress Test for all nine quarters. • Designed and implemented model monitoring framework for probability of the default and loss given default models aligned with the principles of regulatory bodies including SR-11-7. This framework allowed the bank to close previous MRAs issued by the FED.• Managed model monitoring execution and used these outcomes to drive new model development within the bank. • Responsible for solving and documenting the analytical requests coming from regulatory bodies, including: Model Validation, Internal Audit, and Federal Reserve.• Evaluated the quality of the data repository portfolio and used this for internal model development and monitoring. • Reviewed model overrides to aid the credit policy team in designing credit guidance.• Calibrated Probability of Default and Loss Given Default models to be reactive to the economic cycle.• Managed the relationship with Moody’s to ensure the compatibility of their models for their portfolio.• Performed stress testing and scenario analysis for Probability of Default and Loss Given default models Show less

Data Scientist

• Sep 2006 - Sep 2012

Built statistical credit risk models for commercial and consumer portfolios (credit cards, auto, mortgage, small business, and consumer loans) • The credit risk models developed were approved by the local regulator, making BBVA Bancomer the first bank to be IRB compliant in Mexico. Moreover, the models also helped to reduce the credit loan origination process by 25%. • Led meetings with end-users and incorporated their needs to make the statistical models practical and functional while remaining in compliance with regulatory and industry standards. • Calibrated credit risk models to reflect the cycles in the economy. • Monitored model performance and implemented interventions to improve performance. • Work with FICO to develop an account management credit score. Show less

Market Risk Analyst

• 2006 - 2006

Actuarial Analyst

• 2004 - 2006