With the intent of achieving a concrete objective, I contribute an ability to synthesize and integrate heterogeneous information while identifying gaps in information, resolving those gaps, and crafting the conclusions to be accessible to a broad audience. My focus is to understand—and resolve—the disconnect between how something should operate and how something does operate. Because generating a solution requires simplification, I approach problems with the motivation to ethically manage the risks that could adversely impact the intended purpose and the people involved. My strategic objective is to enforce sound standards for the ethical use of quantitative data while evaluating the alignment of model output with the intent. Statistical models should not mislead anybody nor inhibit an individual’s potential.
Achieving my objective draws on my core skills in managing complex information environments with coherent conceptual development, compatible analytics, and valid measurement. In my current role as Model Validator in Model Risk Management, my primary responsibility is to scrutinize the model lifecycle and provide guidance for model development. I determine if the risks are acceptable for the business purpose and for the people that decisions impact. To do so, I have a deep awareness of the data generating process, data sources, emerging technology, and analytical development of traditional and contemporary statistical methods, including natural language processing, machine learning, and generative artificial intelligence. As part of a team, we review and approve every statistical model before it is permitted to enter production. The purpose is to manage and address the risk of adverse consequences that is inherent to all statistical models used to make business decisions. This all aligns with the regulatory guidance developed in SR 11-7 and SR 22-8 under the Federal Reserve and Department of Treasury.
Prior to employment in the financial industry, I was an academic researcher with support from both the German and US National Science Foundations and with extensive career experiences in Asia, Europe, Latin America, and the US. While collecting original data from the government archives in Latin America, for example, I interviewed in a non-native language a former president of Bolivia, the former president of the 2008 Ecuadorian constitution assembly, and more than 100 legislators. I’ve been individually responsible for the complete project lifecycle in both native and non-native languages with publications in multiple peer-reviewed, quantitative journals.
All of these contributions animate my ability to understand risk broadly, identify gaps, lead colleagues, and control risk. I’ve designed and presented on AI Ethics to industry colleagues while also providing peer review for the AI Frameworks & associated Job Aids. This includes responsibility for the analytical design of testing models for disparate impact. I apply my experience in theory-driven empirical research, data analysis discipline, and high standards for measurement validity to ensure that the models I review always exceed the demanding ethical and analytical standards I set for myself and the organization.