Alessandro Miola
Data Engineer - External Service Provider At European Commission's JRC
Ispra, Lombardy, Italy
Summary
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Rockstar🎓
Top SchoolAlessandro Miola is a data engineer with eight years of quantitative and Python-focused experience, currently supporting the European Commission's JRC through Piksel. Trained in mathematical engineering and deep learning, he has transitioned from quantitative credit risk and analytics roles into software and data engineering, blending rigorous modelling skills with production-oriented Python development. An open-source enthusiast, he has contributed practical fixes to a well-known PyTorch learning repository to keep models reproducible with current torchmetrics versions. Fluent in Italian and English with intermediate French, he is pursuing best practices in software and data engineering and is open to Python/data roles across Europe. Notably, his background in quantitative finance gives him an uncommon edge for building reliable, model-driven data pipelines.
8 years of coding experience
3 years of employment as a software developer
Master of Science (MSc) Mathematical Engineering - Quantitative Finance, Master of Science (MSc) Mathematical Engineering - Quantitative Finance at Politecnico di MilanoMaster in Deep Learning - Experis Academy, Master in Deep Learning - Experis Academy at Deep Learning ItaliaDigital Gold Institute
Italian, English, French
Stackoverflow
2,836reputation
152kreached
88answers
5questions
machine-learning
top-5%
scikit-learn
top-5%
python
top-5%
Github Skills (22)
pytorch10
machine-learning10
deep-learning10
optim9
optimizers9
python9
weight9
optimizer9
decay9
model-optimization9
adam9
scikit-learn9
dropout9
computer-vision8
neural-network6
Programming languages (8)
Github contributions (5)
mrdbourke/pytorch-deep-learning
Dec 2022 - Jan 2023
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Role in this project:
ML Engineer
ML EngineerContributions:6 commits, 3 PRs, 1 comment in 1 month
Contributions summary:Alessandro primarily contributed to aligning the project with the stable versions of the PyTorch library's metrics and fixing typos related to model components and hyperparameters within the context of a deep learning project. Their work involved updating code to reflect the latest versions of `torchmetrics` and ensuring the correct configuration of models, including learning rate, weight decay, and dropout settings. The commits focus on maintaining the accuracy and replicability of deep learning models.
pytorchzerodeep-learningmachine-learningzero-to-mastery-course
AlessandroMiola/BitcoinBlockchainTechnology
Jun 2018 - Feb 2019
Material for the Bitcoin & Blockchain Technology course
Contributions:56 pushes, 19 branches, 6 comments in 8 months
blockchain-platformblockchainblockchain-networkcryptocurrencyblockchain-technology
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