I am Vincent, a computer science engineer with a master’s degree, specializing in algorithmics, automation, and artificial intelligence (AI). My professional focus lies in leveraging these passions to drive growth and innovation.
This website is intentionally simple and developer-friendly (no build, no framework).
As a seasoned data scientist with a master’s in computer science, I excel in deciphering complex datasets to derive actionable insights for companies. My proficiency extends from collecting and cleaning data to advanced analytics for informed decision-making.
While I’m deeply passionate about AI, I believe in the importance of algorithmics and optimizing data processing techniques. AI is powerful, but should be applied only when it aligns with core objectives.
My name is Vincent Fischer. I’m what people call a geek: I enjoy everything related to science, which led me to my engineering degree.
I live in Watermael-Boitsfort (Brussels, Belgium). I’ve played rugby, been a scout, worked in social projects, and lived in colocation — experiences that shaped my teamwork and social skills.
Python, Excel, VS Code, Jupyter Notebook, Postman, Pandas, Matplotlib, Numpy, Rest API, GraphQL, WSL, SQL, PySpark, Power BI, GitLab, Docker, Airflow, FastAPI, NLP, ML, Selenium, AWS, Azure, MySQL, Psycopg2
GitHub, image processing, web scraping, Mediapipe, Tensorflow, Keras, Scikit-Learn, VirtualBox, Google Colab, Ansible, Llama2, Godot 4
Oracle, NoSQL, MongoDB, Neo4j, Django, Flask, Laravel, Angular, Symfony, React, HTML, CSS, PyTorch, Databricks, Azure Data Factory, C#
Initiative taker, quick learner, self-taught, team player, volunteer, persevering, curious, autonomous
Some additional projects can’t be disclosed yet (not my IP / still in progress).
I don’t want to emphasize certifications. If you really want to see them, feel free to check my LinkedIn.
Everyone has their own definition of these positions. The goal is to align on what I mean by each role.
Even within the same company, titles can have different meanings. This page clarifies how I interpret each role so we can communicate precisely (and avoid buzzword confusion).
A data analyst extracts insights through thorough analysis, identifies trends/patterns, and creates understandable reports using SQL and tools like Power BI / Tableau / Excel.
A data engineer builds and maintains pipelines (ETL/ELT), structures datasets for analysts/scientists, and optimizes reliability and performance — enabling data exploitation across the company.
A data scientist goes beyond descriptive analytics to build predictive models and solve problems using statistics, ML, and diverse data sources (including computer vision and NLP when relevant).
I work as a data scientist. If the opportunity matches the scope above, feel free to contact me on LinkedIn.