Dr. Juan Camilo Henao Londono

Investor and stakeholder reporting, Group level risk projects, and the management of Risk data, tools, and data governance. Focus is on optimizing regulatory and standard reporting for international institutional investors and rating agencies. Portfolio selection for securitization and replenishment processes is also being conducted. Automated plausibility and data quality checks are being performed, along with the execution of ad hoc analysis requests from institutional investors and internal stackeholders

Business-related data analyzed to report on or enhance key factors pertaining to the customer-company interaction. Python actively applied in various data science projects across the company. Improve the Google AdWords conversion import process from externally attributed conversions to enhance the selection of users for product advertising. Implementation of an uplift model to prioritize customers for contact by our sales team. Collaboration with senior data scientists to implement code for the company.

Enable the practical application of acquired knowledge in a central bank-specific context.

In the summer semester (April-September), to prepare the solution of the exercises of the econophysics course to explain to the students. In the winter semester (October-March), to prepare, to lead laboratory sessions and to grade the reports of the advance laboratory “statistical time series analysis”

To prepare, apply and grade tests, experiments and laboratory reports. To prepare and dictate class, lead laboratory sessions and direct group work.Teach one or more subjects to bachelor students (theoretical physics, physics laboratory, calculus).

To prepare, apply and grade tests, experiments and laboratory reports. To prepare class, lead laboratory sessions and direct group work.Teach one or more subjects to bachelor students (theoretical physics, physics laboratory, calculus).

Econophysics: analyzing market microstructure with methods of statistical physics Time evolution of the market response

Surface roughness estimation by 3D stereo SEM reconstruction