MHP – A Porsche Company

- Developing multimodal Retrieval Augmented Generation applications on company data with Large Language Models
- Building an LLM-based Quality Evaluator and ML-based Duplicate Detection Method for Software Bug Tickets

Data Scientist

Bosch Power Tools

- Implementation and evaluation of probabilistic deep learning models for demand forecasting on AWS SageMaker

Master Student Data Science

- Development of a tool for automated data analysis and visualization in SAP Analytics Cloud
- Implementation of time series forecasting and outlier detection models

Working Student Data Science

Mercedes-Benz AG

- Speeding up the assembly process by using machine learning to predict throughput times and errors on Azure Databricks
- Automation of graph visualization for the optimization of assembly analysis

Fraunhofer IPA

- Implementation and evaluation of a generative deep learning model for image data augmentation for cutting edge patterns
- Implementation of scientific papers in Python

Bachelor Student Deep Learning

MAHLE

- Analysis of engine data and application of machine learning for prediction in piston temperature measurement

Intern Data Analysis & IT Project Management

I make learning Data Science effortless for you | Data Science @ Bosch

Hi 👋🏻
I'm Banias, Data Scientist at MHP.

Applying new technologies and methods in Data Science is my passion.

Through my experience and continual learning, I've gained valuable insights and tips that I love sharing with Data Scientists, Machine Learning Engineers and builders like you.

If you're looking for practical advice, helpful resources, and articles on the latest trends or best practices in the field, you're in the right place.

Let's connect and stay updated on the exciting world of Data Science together. Feel free to reach out, read my articles, and let's grow our knowledge and network. :)


Note: My views are my own and don‘t represent my employer.

Banias Baabe

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.

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! 🤗

taplio

The Battle

Banias Baabe

👋 Luca Baggi

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