xtream - Digital Products & AI Solutions

Build state-of-the-art AI solutions.

• Read and evaluate the latest innovations in the Large Language Model literature.
• Develop infrastructure to enable AI-powered products, such as token compression algorithms and  guardrails for GenAI applications on Kubernetes.
• Developer relationship with the local Python and AI Communities.
• Support my colleagues in applying and presenting to local events and Python conferences.
• Host of AI Compass, a podcast featuring well-known Data and AI managers to provide C-level and developers the tools to build AI-powered solutions.

AI Engineer

Università degli Studi di Milano

• Coding for Data Science - R Labs (2022/2023, MSc in Data Science and Economics). Building reproducible environments with {renv}, comparing base R and the Tidyverse, introduction to Shiny dashboards.

• Advanced Multivariate Statistics - Python Labs (2022/2023 + 2023/2024, MSc in Data Science and Economics). Multioutput regression and classification with scikit-learn, Gaussian Mixture Models, non-linear PCA and other multivariate models with statsmodels.

• Assistant lecturer in Statistics for Business Decision Making (2021/2022, 2022/2023, 2023/2024, BSc in Economics and Management). Clustering and PCA, logistic regression, tree-based methods and introduction to time series analysis and forecasting (auto-regressive models) with R.

• Statistics for Big Data in Economics and Business (2021/2022, BSc in Economics and Management). Teaching Python and PyData stack (Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn, Statsmodels) to a class of 100+ sophomores. Logistic regression, clustering, principal component analysis (PCA); model validation techniques.

Teaching Assistant in Statistics and Machine Learning

Futura

Building the relational database that powers the platform's backend, using Flask, SQLAlchemy, and Alembic to manage migrations. Will create new data pipelines and implement a modern data stack for data engineering, and put into production machine learning models to forecast student performance and recommendation engines to serve questions.

Machine Learning Engineer

Occupy AI

• Working on a computer vision project for a partner firm in the field of installation of photovoltaic solar panels (IPV).
• Managing over 400GB of satellite pictures; developing a feature-engineering based strategy to improve the labels that came with the data.
• Exploring external data sources (e.g. OpenStretMaps) to enrich the data.
• Creating internal software libraries to connect with remote storage sytems (e.g. DropBox).
• Serving models with FastAPI and Streamlit dashboards.

Data Scientist

European Central Bank

• Big data analytics with Hadoop and Impala.
• Getting into cloud computing with Cloudera Data Science Workbench and PySpark.
• Supporting Economists in data retrieval exercises, scripting for querying APIs, string matching and record linkages.
• Spreading version control and contributing to internal documentation.

Trainee Data Analyst and Research Assistant at Directorate General Research

Il Post

• Introduction to macroeconomics and finance for private investments.
• Guide to loans regulations in Italy.
• Data Journalism: Is Italy the country of savers we were always told?
• ETF, trade in commodities, ESG criteria, crowdfunding investment.
• Fintech, Bitcoin and cryptocurrencies.

Economics and Finance Reporter

Machine Learning Engineer by day and open source maintainer by night, as part of my job I craft systems to make LLMs go brr. Oh, and I am a huge Polars advocate 🐻‍❄️

I have been a speaker at several Python conferences in Europe, and taught machine learning, statistics, and programming at the University of Milan. With a great team of volunteers, I organise events for Python and PyData communities in Milan every month. Previously, I also worked as a journalist, honing my writing skills while explaining economics, finance and econometrics. Feel free to reach out! 🤗

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