I build dashboards, data pipelines and analyses that turn raw data into decisions.
Data Science student · Exchange year at the University of Illinois Springfield · Springfield, IL
I am a Data Science student at IUT2 Grenoble (Université Grenoble Alpes), specializing in data visualization and decision-support tools. I am spending the third and final year of my degree at the University of Illinois Springfield.
What I enjoy most is the full chain: collecting and cleaning raw data, modelling it, and delivering something a decision-maker can read at a glance. During my internship at Amundi, Europe's largest asset manager, I put that into practice with Power BI dashboards and an automated Python pipeline that are now used in production.
I care about accuracy, clear documentation and tools that people actually use after I leave.
Amundi ESR runs employee savings and retirement plans for companies and their employees. Its Beneficiary Services department generates a large volume of data (calls, emails, complaints) but had no suitable reporting tools.
No data dictionary existed, so I learned the data model by working directly with the business teams and documenting what I found.
Processed 800 to 1,500 client data update requests per day on the Alto ESR platform, following internal banking procedures with strict accuracy and confidentiality requirements.
Supervised groups of children during two 2-week sessions; coordinated with the leader team and ran daily activities under time pressure.
An R Shiny web app presenting a survey of about 4,000 university students on how they use generative AI, across 4 themes: usage, trust and ethics, learning methods and digital skills.
For the Université Grenoble Alpes campus planning department: wrote the requirements, built a field data collection tool in ArcGIS Online, collected data on site, then delivered reporting dashboards, cost estimates for compliance work and a StoryMap presented to the client.
Designed a data warehouse for a school transportation company (customer profiles, monthly sales, failed payments): data dictionary from CSV, Excel and XML sources, star schema, ETL flows in KNIME, MySQL implementation and analytical SQL queries.
Analyzed 3.9 million New York City taxi trips (NYC TLC, April–May 2023): identified weekly seasonality, decomposed trend and seasonality, compared regression with Holt-Winters exponential smoothing, selected the model by RMSE and produced a 7-day forecast.
Started as a Python script automating stock and ETF price history with comparative charts, then rebuilt as a multi-page Dash app on a SQLite database, with market data from yfinance and reconciliation against my brokerage export. Core logic covered by 40+ automated tests.
Cleaned open datasets and applied regression models in R to analyze CO2 emissions; built interactive Tableau dashboards and a technical report.
Collected data from the Rebrickable (LEGO) REST API in Python, handling pagination, and generated static HTML reports by theme from an interactive menu.
Audited the data collected in the previous project against GDPR (EU data protection) obligations, with a risk analysis and a recommendations report.
Fall 2026 courses: Data Visualization (CSC 562), Introduction to Database Systems (CSC 472), Data Structures and Algorithms (CSC 385), Money, Banking and Financial Markets (ECO 335), Introduction to Macroeconomics (ECO 202).
Relevant coursework: reporting tools and business intelligence systems, SQL database design and data warehousing, data preparation and integration, automated statistical programming, hypothesis testing, linear models for decision support, factor analysis and clustering, web programming.
1600 Elo on Chess.com; strategy and long-term planning, playing since 2021.
Five years of consistent training, including calisthenics.
Self-taught since 2025, weekly practice.