Ernesto López Fune, Phd Email & Phone Number

Paris, Fr

Paris, Île-De-France, France

Paris, Île-De-France, France

* Lead Data Scientist, driving AI research, data anonymization, and XAI initiatives.* I oversee talent acquisition, team development, knowledge transfer, and mentoring of interim students.* PO of NexiaSynth, a data anonymization platform and PO of the chatbots MaineCoon tailored for financial services.

Paris, Île-De-France, France

* Developed a back-testing platform for PD, LGD, and CCF risk models within the Model Risk Management team.* Built and prepare data sets using Dataiku and PostgreSQL for the analysis of ECB-regulated KRIs.* Backend development on R and implemented and automated unit tests on Python.* Designed and implemented modules of the platform’s UI on R-Shiny.* Presented the platform's progress and introduced new features during weekly meetings to the product committee.* Technical Environment: Dataiku, PostgreSQL, R, Python, VS Code, R-Shiny, Git, Agile methodology.

París, Isla De Francia, Francia

* Provided data-driven support to the Risk Management Department.* Developed a Python-based agent simulation to model the life cycle of settlement instructions, which supported the ICLAAP team in conducting stress tests and analyzing domino effects in case of account defaults.* The simulation managed large data volumes (+100 GB) related to settlement activities, CAGs, collaterals, and exposures, achieving a precision rate of 98%.* Created ETL services in Python for financial data analysis and reporting using Hadoop (Cloudera) and SQL databases.* Developed and monitored a Power BI dashboard CCP Journal for daily monitoring of settlement activities of CCPs like LCH, LME, ICE Clear, and Euronext Clearing.* Developed and monitored a Power BI dashboard Euroclear’s News Journal for weekly tracking of financial sentiment on Euroclear Bank, powered by a sentiment analysis engine.* Technical Environment: Python, Power BI, Hadoop (Cloudera), SQL, Agile framework.

Paris, Île-De-France, France

* Implemented ML pipelines to automate financial processes such as invoice categorization and cash flow forecasting.* Designed and integrated robust pipelines for classification using CatBoost in Python, achieving an AUC of 96%.* Optimized an exponential smoothing model to enhance forecasting accuracy in cashflow predictions, reducing the error margin to below 4%.* Collaborated with the DevOps team to dockerize services, facilitating deployment and ensuring continuous integration.

Paris, Ile-De-France, France

* Enhanced prediction of graft survival probabilities after kidney transplants using machine learning models adapted to handle right censored data.* Prepared three datasets: a derivation cohort of 4000 recipients in France recruited between 2005 and 2014, and two validation cohorts with 3557 recipients from Europe and North America recruited between 2002 and 2014.* The c-statistics of some models reached 86% and 88%, surpassing the iBox model’s 85% (an internal model using Cox’s Proportional Hazards), though the difference was not statistically significant.* Technical Environment: Python, R, Git, Agile framework.

Paris Area, France

* Managed predictive analytics for the H2020 European research project FINSEC.* Lead the project’s technical aspects and facilitating cross-functional collaboration.* Communicated progress and strategies to consortium members and prepared roadmaps for predictive analytics initiatives.* Conducted internal training on innovation and big data topics.* Developed and integrated multiple use cases, such as anomaly detection for LiberBank and identifying recurring behaviors for Nexi.* Technical Environment: Python, MongoDB, VS Code, H2O.ai, Git, Docker, Flask, Agile framework.

París Y Alrededores, Francia

* Supported particle detection analysis for dark matter WIMPs in the Xenon1T detector.* Implemented Monte Carlo simulations in C++ to optimize the geometric shape of the fiducial volume with minimal noise.* Analyzed collision data and conducted back tests of particle collision models.* Author of several articles in high-impact physics journals, including Physical Review Letters and Nature.* Technical Environment: Python, MongoDB, VS Code, C++, Git, Agile framework.

Trieste Area, Italy

Completed a Ph.D. thesis focused on Dark Matter and Rotation Curves of spiral galaxies, involving extensive data analysis of galaxy rotation curves using astrophysical measurements. Developed and maintained the software package DMROT in Wolfram Mathematica, enabling non-linear regressions, power-law correlation searches, and high-quality plot creation for a substantial database of galaxy rotation curves. Introduced an empirical method to address the local dark matter density problem, predicting virial radius, masses of spiral galaxies, and maximum rotational velocities. Conducted in-depth analyses of astrophysical data and galaxy images to extract stellar and gaseous mass contents. Investigated modified theories of gravity's phenomenology concerning Dark Matter. Authored and published articles, presented in seminars, and contributed to progress reports. Engaged in independent research beyond ongoing projects.

Trieste, Italy

I conducted groundbreaking research in particle physics, focusing on the Neutrinoless Double Beta Decay phenomenon and Physics Beyond the Standard Model during my dissertation. My work delved into the neutrino mass generation mechanisms, exploring Seesaw Mechanisms and the Left-Right Symmetry Theory. I performed rigorous analytical and numerical calculations for cross sections and decay rates related to neutrinoless double beta decay and sterile neutrinos. Beyond assigned projects, I actively pursued independent research, contributing to the advancement of our understanding in this complex and evolving field.

Calle 15 Esq E, Vedado, Plaza, C. Habana, Cuba.

I conducted my master's thesis on magnetized strangelets at finite temperature, delving into the realm of phenomenological models in Quantum Chromodynamics. My research spanned topics like Quark-Gluon plasmas, Quark Condensates, Color Superconductivity, Quantum Field Theory at finite temperature, and the applications of Strong Magnetic Fields in Compact Objects. Utilizing Fortran-90, I developed numerical algorithms to solve nonlinear systems of equations, both integral and differential. Additionally, I implemented Molecular Dynamics simulations for solids in C++, employing the Velocity-Verlet algorithm. Complementing my research, I shared my knowledge by teaching tutorial lessons on Ordinary Differential Equations and Calculus of Variations to second-year students at the School of Physics, University of Havana.

Doctor Of Philosophy - Phd, Astroparticle Physics, 4.0/4.0

Activities and Societies: Astroparticle Physics and Astrophysics department Ph.D. in Astroparticle Physics Data and Statistical Analysis.

Diploma In High Energy Physics, High Energy Physics, 3.9/4.0

Activities and Societies: High Energy Physics and Cosmology department Diploma Student in High Energy Physics Theoretical High Energy.

Master'S Degree, Theoretical Physics, 4.0/4.0

Magnetized strangelets at finite temperature Phenomenological models of QCD Strong magnetic fields in Astrophysics Nuclear physics Quantum.

Bachelor'S Degree, Physics, 3.8/4.0

Completed in parallel all the credits of the Mathematics career Magnetized strange quark matter in stellar equilibrium Phenomenological.

Bachelor Of Technology (B.Tech.), Accountancy And Finances, 3.8/4.0

3 years+6month stage: Accountancy and Finances Revenues department Asset pricing Capital asset pricing model Independent Price.