Experience

Seedtag

• Spain
• Advertising Services
• 400 - 500 Employee

• Mathematical Software Engineer (Data Scientist)

  • Jul 2022 - Present



EtsFactory

• Spain
• Financial Services
• 1 - 100 Employee

• Data Scientist in the FX Team

  • Jan 2020 - Jun 2022

• Data Scientist in the Equities Team

  • Dec 2018 - Jan 2020



Politecnico di Milano

• Italy
• Research Services
• 700 & Above Employee

• Master Thesis Student

  • May 2018 - Dec 2018



Monash University

• Australia
• Higher Education
• 700 & Above Employee

• Junior Researcher

  • Aug 2017 - Mar 2018

  Research Internship. Project scope: DNS code construction to solve the Navier-Stokes equations in the streamfunction - vorticity formulation. Research Internship. Project scope: DNS code construction to solve the Navier-Stokes equations in the streamfunction - vorticity formulation.



Delft University of Technology

• Netherlands
• Research Services
• 700 & Above Employee

• Teaching Assistant

  • Feb 2017 - May 2017



Fokker Services Group

• Netherlands
• Aviation and Aerospace Component Manufacturing
• 300 - 400 Employee

• Design Competition

  • Feb 2017 - May 2017

  Knowledge Based Engineering competition at Fokker Aircraft with a Python framework. Put together in teams the structural, aerodynamical and economical performance of a business jet with a Python-based KBE platform. We had to input all the design equations and constraints such that the external and some internal parts of the aircraft geometry were generated in real-time. Additionally, if the user tried to set a forbidden design condition, the code was able to recover and find the closest bound. We were finalists, but the jury made a special distinction for our user input interface. Through an XML tree read inside the code, the user could trim all the starting design variables. References for the Python-based platform: ParaPy, https://www.parapy.nl Show less



Fluid Mechanics and Combustion Department, ETSIAE (UPM)

• Madrid Area, Spain

• Undergraduate Research Assistant

  • Sep 2015 - 2016

  As a part of a Research Grant given by the Regional Government of Madrid to encourage undergraduate research, I worked for Miguel Hermanns in his Geothermal Energy project. The goal of the research assignment was to update the numerical method used in the determination of the steady-state temperature distribution of the ground for a given geothermal installation. The main challenges where the computational time required by the direct solver and the large storage capacity demanded by the In order to do so, to solve a partially filled-in matrix arising for the discretization of a integro-differential system had to be solved. This matrix had a low sparsity level, thus slowing down all the operations and requiring Gigabytes of storage. To solve the problem, we implemented a Krylov subspaces-based iterative solver with a physics-based preconditioner. The former works with matrix-vector products, removing the storage difficulties. The latter accelerated the convergence of the method, making it competitive for the problem's application. The most beautiful part of the project was the construction of the preconditioner. I learned a lot about algebra and important concepts regarding the discretization of a system of ODEs. Additionally, at the end of the project we made use of a new variety of interpolation nodes introduced by Prof. Hermanns, in order to increase the interpolation degree of the FD discretization. Because of the integral operator, we had to go around some hidden floating point errors hidden in classical Numerical Analysis formulas that only arise when the interpolation degree is high enough. This project was converted into my Final Bachelor Assignment, to which the thesis committee assigned the highest possible result, 10/10. Show less



Ejército del Aire

• Spain
• Defense and Space Manufacturing
• 700 & Above Employee

• Summer Internship

  • Jun 2015 - Jul 2015

  Coordination of helicopter maintenance tasks. Coordination of helicopter maintenance tasks.



Applied Mathematics Department, ETSIAE

• ETSIAE, Plaza del cardenal Cisneros, Madrid, Spain

• Internship Trainee

  • Jan 2015 - Jun 2015

  Finite volume method (FVM) learning and mathematical modeling of a Langmuir trough experiment. Finite volume method (FVM) learning and mathematical modeling of a Langmuir trough experiment.