Alex Chauvin, PhD

Performing multi-omics data analysis for translational research on Pancreatic Ductal AdenoCarcinoma (PDAC), integrating several omics to identify novel biomarkers and therapeutic targets for precision medicine

As a Statistical & ML Modeling Expert, I developed and deployed machine learning models for financial risk assessment, enabling more precise credit granting decisions for corporate vehicle financing. Beyond model development, I built scalable ML pipelines, optimized data architectures, and integrated data-driven methodologies to improve financial decision-making. 📌 Risk Modeling & Deployment: Built ML models (XGBoost, Bayesian inference) reducing financial risk exposure by 50% while increasing credit approval rates by 20%, 📌 ML Pipeline Automation: Developed end-to-end MLOps workflows (CI/CD, Docker) for scalable model deployment and monitoring, 📌 Frequentist Statistical Analysis: Designed data-driven metrics to assess business introducers’ related risk, 📌 Data Enrichment & Feature Discovery: Integration of new data sources (macroeconomic indicators, alternative financial data) to boost model accuracy, 📌 Tech Stack Transformation: Led migration from old to no/low-code data architecture stack, streamlining data workflows for low-code analytics adoption and improving data integration workflows for models

- Manager of a five members data science team, - Study and forecast of companies payment behaviour using machine learning (Randomised forest models, NNs, Time Series), - International companies scoring on financial solvency and B2B risks (conformity, corruption, ESG), - Data sourcing techniques development and pipeline setups, - Relational databases (MySQL, MongoDB, redis, elasticsearch) management in a cloud environment (AWS)} management in a cloud environment (AWS)}

• Title: Low-Mass dimuons study at forward rapidity in pp collisions at √s = 5.02 TeV with the ALICE collaboration • Extraction of low-mass mesons and study of the strangeness enhancement • Expertise of the muon-chamber tracker and trigger • Tutoring of experimental Physics • Attending PhD school and PhD classes: experimental studies of QGP, Pythia8

• Research assistant position in the ALICE collaboration • Study of the Quark Gluon Plasma with low mass dielectrons • Investigation of the dielectron mass spectrum with RUN II data • Special focus on the rejection of photons conversion using machine Learning (TMVA) • Service Task: Online Calibration of the Time Projection Chamber using the High Level Trigger

Tutor in Mathematics, Physics and Chemistry : Teaching of middle/high school and Bachelor students

Prospects of extra dimension phenomena in the diphoton channel with the ATLAS detector. Tools used: - ROOT5 - PYTHIA6/8 - BAT (Bayesian Analysis Tool)

Study of Silicon Photo-Multipliers (SIPMs) for the MAGIC experiment Tool: - Labview

Visits of laboratories and experiments carried out on scintillators, and photomultipliers

Study of ongoing research on the Higgs boson at the LHC

Production of thin films by sputtering deposition and characterisation of the deposits