Data Scientist · Machine Learning & NLP
As a data scientist with two years of work-study experience in the banking sector, I have had the opportunity to work on projects where data has a direct impact on the business: evaluating the effectiveness of marketing campaigns, detecting transactions to crypto platforms, and optimising and automating credit risk and fraud reporting.
What drives me is both the technical depth of a well-designed model and the tangible impact it can have on operational business decisions. I’m particularly drawn to the fast-evolving nature of the field: tools keep improving, and the solutions we build are becoming increasingly ambitious. This constant need to adapt is both an intellectual challenge and a source of motivation for me.
I’m now looking for my first full-time role as a Data Scientist or AI Engineer, in a stimulating environment where I can continue to grow and take on new challenges.
Experience
Click on an experience to see the details.
Blog
Field notes, tutorials and reflections on Data Science in production.
How Andrew Ng's Deep Learning Specialization bridged the gap between academic theory and the practice of deep learning.
A hands-on account of training a reinforcement learning agent: the dead ends, the right tools, and the lessons you can only learn by doing.
How our team designed a RAG pipeline to transform a university help center, and what I learned leading four developers under time pressure.
Portfolio
Real problems, real data, measurable results.
Chatbot that turns cloud infrastructure requirements into Terraform with real-time cost estimates.
Deep reinforcement learning agent playing the 2048 game using MaskablePPO, a custom CNN and reward shaping
Realistic satellite image generation from road and building segmentation masks
Multi-agent voice assistant for the restaurant industry, with multilingual support, phone integration, RAG and analytics dashboard
Intelligent BI pipeline developed during an IBM hackathon: semantic search, RAG and analytical dashboard
Per-session revenue prediction for the Google Merchandise Store using Google Analytics data