Freelancer profile translated to English.

Description

Data Analyst specialized in data analysis and statistical modeling, I help companies leverage their data to derive clear and actionable insights for decision-making.

As part of my work-study program at SNCF Voyageurs (Marketing & Services – Transilien Division), I am involved in monitoring and analyzing the quality of service provided and perceived, in line with the contract between SNCF and Île-de-France Mobilités. I work on about thirty key indicators related to services offered to travelers (punctuality, passenger information, cleanliness, equipment availability, customer satisfaction via BaroGare and perception surveys), which feed into a bonus/malus system.

My role involves ensuring data reliability and structure, performing advanced statistical analyses, and developing forecasting models to anticipate changes in passenger satisfaction and perception based on the quality of services offered.

I use Python and R (RStudio) for data processing and modeling, as well as Power BI for creating interactive dashboards for effective performance management. I have also implemented machine learning approaches applied to time series (ARIMA, Holt-Winters) to identify trends and produce evolution scenarios.

In addition, I develop automated tools in Excel (Power Query, VBA) to consolidate data, improve its reliability, and facilitate its use.

My missions:

• Data analysis and processing (Python, R, Excel)

• Statistical modeling and forecasting

• Dashboard creation (Power BI)

• Process automation (VBA, Power Query)

• Performance analysis and decision support

Rigorous, autonomous, and results-oriented, I adapt to your needs to provide reliable, clear, and directly usable analyses.

Languages

French
Native or bilingual
English
Conversational

Workplace preferences

Remote only

Primarily works remotely

SNCF Voyageurs
Analysis of Provided and Perceived Quality
September 2025 - Today (11 months)
Saint-Denis, France
As part of the contract with Île-de-France Mobilités, I support the Contract & Performance department of Transilien in monitoring, analyzing, and enhancing the quality of service provided and perceived.

I work on about thirty indicators related to traveler services (equipment availability, cleanliness, passenger information, mystery shopper surveys, satisfaction via BaroGare and Perception Survey), which feed the bonus/malus system between IDFM and Transilien.

My role involves ensuring data reliability and structure, performing in-depth statistical analyses, and developing forecasting models to anticipate changes in passenger satisfaction and perception based on the quality of services offered.

To achieve this, I use Python and R (RStudio) for data processing, modeling, and time series analysis, as well as Power BI for creating interactive dashboards that facilitate performance management.

Notably, I have implemented machine learning approaches applied to time series data (ARIMA, Holt-Winters), enabling trend identification, variation smoothing, and the production of evolution scenarios for service quality indicators.

Finally, I develop automated tools (Excel, Power Query, VBA) for data consolidation, improved reliability, and the provision of clear, actionable analyses to support strategic decision-making.
Microsoft Excel Python RStudio Microsoft Power BI
Sncf Voyageurs
QUALITY AND REPORTING OFFICER
September 2024 - September 2025 (1 year)
Saint-Denis, France
During my work-study program at SNCF Voyageurs (Marketing and Services Division – Transilien), I joined a team dedicated to monitoring service quality and performance. My role was to analyze and utilize data from performance indicators related to service quality, within the framework of the contract with Île-de-France Mobilités.

I participated in the design and automation of analysis tools to track the Bonus/Malus mechanisms, used to evaluate the performance of transport lines. These tools, developed in Excel (Power Query, VBA) and Power BI, consolidate, structure, and visualize complex data to facilitate decision-making in strategic meetings.

I also conducted statistical analyses and forecasting models (ARIMA, Holt-Winters) on time series data to anticipate indicator evolution and optimize performance.

This experience allowed me to develop strong expertise in data processing, statistical modeling, and data visualization, while addressing concrete business challenges related to performance and service quality.
Microsoft Excel Microsoft Power BI RStudio
Worldpanel by Kantar
Data Scientist
April 2024 - April 2024
Chambourcy, France
Data Science internship at Kantar Worldpanel, within the Analytics Statistics team.

Conducted consumer data analysis for marketing studies (Panel Voice), including customer segmentation, discriminant analysis, and processing of questionnaire data.

Implemented advanced statistical methods (AFC, CAH) to identify purchasing drivers and improve customer satisfaction.

Participated in assortment optimization projects (Assortment Optimizer) to identify key products and maximize commercial performance.

Tools used: R, Excel, Azure, Power BI.