CV

AI Software Engineer

Schneider Electric

As an AI Software Engineer at Schneider Electric, I am involved in the development of innovative solutions to enhance industrial processes and improve operational efficiency.

• Deployment of a cloud-to-edge RAG (Retrieval-Augmented Generation) system for industrial procedure explanations, enabling real-time access to information.
• Packaging of Python libraries to reduce the licensing issues of the RAG system, ensuring compliance with proprietary license.
• Creation of self-extracting archives on Ubuntu cross-compatible with Windows

Adjunct professor

IUT de Paris - Rives de Seine

Alongside my work as a Data Engineer, I teach at my former school, working with students in Data Science Bachelor.

• 2nd year – Object-Oriented Programming in Python
• 3rd year – NoSQL & Database Migration

Data Platform Engineer

Servier

The Data Factory, through specialized Feature Teams, enhances financial monitoring via analytical dashboards. The Data Platform integrates and processes data from diverse sources using advanced tools like BigQuery and dbt. Key activities include ELT pipeline development, real-time data updates, and comprehensive support for data analysts.

• Deployment of 15 dashboards powered by 25 data sources for 1,200 users.
• Management of 50 Power BI datasets, available in self-service Excel for business teams.
• Monitoring of 150+ daily pipelines, ensuring optimal reliability.

Data Engineer / Product Owner

Graal Systems

Graal Systems develops a SaaS platform that automates data infrastructure management, allowing developers to focus on their projects without technical constraints. As Data Engineer & Product Owner, I delivered two key initiatives: a low-code ETL pipeline engine supporting multiple frameworks (e.g. Apache Spark, Apache Flink, Dask), and a scalable activity feed system using Apache Cassandra.

• Developed low-code ETL pipeline engine supporting multiple frameworks (Apache Spark, Apache Flink, Dask, Pandas, Apache Beam) with automated code export, achieving production deployment in 3 months and optimizing test execution time by 92%.
• Designed and deployed scalable activity feed system using Apache Cassandra on Kubernetes, reaching production in 1 month with automated quality controls and enterprise-grade reliability.
• Combined Data Engineering and Product Owner roles to identify user needs, manage product backlog, and deliver cloud-native solutions that democratize data infrastructure management

Data Engineer Consultant

LittleBigCode

As a Data Engineer Consultant at LittleBigCode, I support clients in the design and deployment of scalable data solutions, optimizing architecture, pipeline industrialization, and cloud infrastructure to ensure reliable and high-performance workflows. My expertise spans CI/CD automation and infrastructure (Terraform, Kubernetes), ETL pipeline development (Spark, dbt), and API deployment (FastAPI, PostgreSQL, Apache Cassandra) in both on-premise and cloud environments. I also work on data platform optimization and provide technical support to analytics teams. Passionate about data engineering, I leverage my skills to develop high-value solutions, enhancing system reliability and facilitating access to strategic insights. 🚀

Machine Learning Engineer

Carrefour

Carrefour, a leading French retail giant, is committed to providing quality products and services to its customers. As a Machine Learning Engineer, I contributed to the development of predictive models and data pipelines to enhance financial operations and customer data quality.

• Developed predictive ML models for accounting provisions using time series, random forests, and regression techniques, deployed on GCP (BigQuery, Vertex AI) with automated dashboards.
• Built customer database reconciliation pipeline achieving 100% SIRET matching and 30% address-based matching with INSEE's SIRENE database, significantly improving data quality.
• Optimized financial operations through automated provision management and model selection for direct debit rejection prediction, minimizing losses and enhancing decision-making.

Data Scientist

Conservatoire National des Arts et Métiers (CNAM)

I conducted a comprehensive study on absenteeism related to mental health, specifically focusing on employees with severe depression.

• Modeled absenteeism patterns for employees with severe depression using random forests, decision trees, and logistic regression to identify key risk factors.
• Published research findings in a scientific journal, contributing to understanding of mental health impact on workplace absenteeism.
• Profiled high-risk employees through advanced statistical modeling and data analysis, providing actionable insights for workplace mental health management.

R Shiny Developer

Conservatoire National des Arts et Métiers (CNAM)

As an R Shiny Developer, I created a dynamic visualization tool to identify psychosocial risk factors in the workplace to reduce stress and promote employee well-being. The interactive application provides data-driven insights for workplace risk prevention and decision-making.

• Developed interactive R Shiny application for psychosocial risk analysis using clustering, random forests, and regression models to identify workplace stress factors.
• Implemented comprehensive data visualization tool combining statistical methods with Machine Learning to facilitate workplace risk prevention and decision-making.
• Contributed to workplace well-being research through bibliographic synthesis and data-driven insights for mental and physical health promotion.

President of the association

Ensora

ENSORA is ENSAI's tutoring club, which aims to help students in difficulty and support them in preparing for their exams.

• Planned, coordinated, and led tutoring sessions for students in lower grades, fostering a supportive and effective learning environment
• Gathered and analyzed data on students' academic challenges and needs to tailor tutoring programs and improve educational outcomes
• Recruited, trained, and managed a team of tutors, ensuring high-quality instruction and mentorship for students
• Liaised with school administration to secure and manage room bookings for tutoring sessions, optimizing the use of school facilities
• Developed and implemented strategic session schedules, particularly during exam periods, to maximize student preparation and performance
• Executed comprehensive communication strategies to promote upcoming sessions, utilizing email and social media platforms to engage students
• Established and managed an official email account for the association, streamlining communication and maintaining professional correspondence

Tutor

Ensora

As a volunteer tutor, I helped lower-level students overcome their difficulties in statistics and computer science. I organized tutoring sessions, prepared exercises and review sheets, and created educational resources to facilitate their learning.

• Delivered engaging and effective tutoring sessions, employing a variety of teaching methods to cater to diverse learning styles and needs
• Designed and developed comprehensive session plans, including exercises and past exam papers, to ensure thorough preparation and reinforce key concepts
• Created and distributed customized worksheets and learning materials to supplement tutoring sessions and facilitate student understanding and retention
• Curated and distributed educational resources, including student-created notes and course summaries, to enhance learning materials and support student success

Engineering degree (Diplôme d'ingénieur)

Ecole nationale de la Statistique et de l'Analyse de l'Information (ENSAI)

Big Data and Data Engineering

• DevOps
• Software engineering
• Cloud computing
• SQL and NoSQL
• Object-oriented programming

DUT STID (Statistique et Informatique Décisionnelle)

IUT de Paris - Rives de Seine

Data Science Bachelor

• Statistics
• Machine Learning
• Time series
• Relational databases
• Statistical programming