Experience

• AI Engineer

  Stealth Startup • Remote

  2025-06 – 2025-09

  • •For an undisclosed stealth fintech start-up that recently raised 4M$ I worked as an AI Engineer where I,
  • •Contributed to their full-stack app, including a critical feature that landed my client an important lead.
  • •Rewrote their RAG system from scratch to be state-of-the-art, including chunking, embedding, retriever and metadata system, our performance went from 50% to 100% on their baseline use case.
  • •Contributed to Data Engineering workflows, so their document ingestion pipeline would be seamless, incremental and fast.
  • •Implemented industry-standard DevOps practices making their deployments automated, fast and safe.
  • •Tech stack: Python, LangGraph, Pydantic AI, OpenAI, Azure, BAML, Dagster, RAG, Azure Cognitive Search, React, FastAPI,
• AI Engineer

  Albert School • Remote

  2024-07 – 2025-02

  • •At Albert School, I engineered cutting-edge AI solutions to optimize student success. As a freelance AI Engineer, I:
  • •Designed and implemented an advanced Generative AI-powered agentic system that could detect students' subject interests, autonomously select promising topics, and deep dive into relevant concepts
  • •Developed a sophisticated agent architecture that generated personalized learning paths along with custom educational content and assessment quizzes to validate student understanding
  • •Architected a robust agentic backend leveraging LangChain, LangGraph, and BAML, with data persistence handled through Supabase integration
  • •Built an intuitive user interface using Streamlit that provided students with seamless access to their personalized learning experiences
  • •Developed RESTful API endpoints using FastAPI to enable communication between the agentic backend and frontend components
  • •Collaborated with educational experts to refine the system's ability to align AI-generated content with pedagogical best practices
  • •Managed the whole infrastructure on a dedicated server using docker-compose
• Data Scientist

  OpenClassrooms • Remote

  2023-10 – 2024-02

  • •At OpenClassrooms, I leaded data science initiatives to enhance the student conversion lifecycle. As a freelance Data Scientist, I:
  • •Conducted in-depth analysis of the student conversion funnel, identifying key optimization opportunities and implementing data-driven solutions
  • •Developed a sophisticated survival analysis model to predict long-term conversion patterns, accounting for the extended decision-making journey of prospective students
  • •Collaborated with cross-functional teams to integrate analytical insights into strategic decision-making processes
  • •Delivered actionable recommendations to Head of Data and CTO that improved student engagement metrics and optimized marketing resource allocation
  • •Baked my work into an Airflow Data Engineering pipeline to compute predictions on a daily basis
• Data Scientist

  Inato • Remote

  2023-08 – 2023-09

  • •At Inato, I led a strategic data science initiative to optimize marketing efficiency and enhance lead conversion rates. As a freelance Data Scientist, I:
  • •Conducted comprehensive analysis of the marketing team's lead database, implementing advanced data cleaning and segmentation methodologies
  • •Developed and deployed a lead prioritization model that successfully identified the top 10% of high-value prospects
  • •Collaborated closely with marketing stakeholders to implement data-driven targeting strategies
  • •Delivered actionable insights that significantly improved marketing efficiency and increased quality lead conversion rates
• Data Engineer

  Alma • Remote

  2022-03 – 2022-12

  • •At Alma, I led the Data Engineering team to build and maintain a modern data infrastructure. The goal was to help business owners make data-driven decisions by improving data quality and providing efficient tools.
  • •I developed custom data connectors and designed layered BI transformations to facilitate data usage. Additionally, I helped recruiting new team members through a rigorous selection process and helped upskilling current team members thus strengthening the group's skills and expertise.
  • •I managed the Data Engineering team, coordinating efforts to build a modern data infrastructure, including an ELT datalake and data warehouse. My role included overseeing projects, managing resources, and communicating with stakeholders to ensure the success of the overall mission.
  • •As the primary support for the Data Science team, I assisted in deploying their models and resolving technical issues encountered.
  • •As the primary support for the Data Analytics team, I assisted in building analytics models, crafting advanced analytics and ensuring maintenance of the data infrastructure.
  • •The mission's outcomes include a notable improvement in data quality and the provision of effective tools for business owners.
• Mentor Data Scientist

  OpenClassrooms • Remote

  2021-11 – 2022-02

  • •At OpenClassroom, I mentored 5 students in Data Analysis and Data Science programs, sharing my knowledge gained from my hands-on experiences, and honed my teaching skills to give them the keys to succeed in their future professional lives.
  • •My mission involved weekly work with the students to ensure they fully understood their courses and applied their skills correctly within the context of their projects.
  • •This first contact with the world of education taught me a lot and gave me great motivation to continue in this field in the long term.
• Data Scientist / ML Engineer

  ManoMano • Paris

  2018-03 – 2020-01

  • •As a Data Scientist at ManoMano, I was part of the Growth & Data team, our mission was to drive growth through smart optimizations and data-driven methods. During my assignment, I mainly accomplished the following,
  • •I developed an algorithm to identify Google keywords to target, optimizing budgets and landing pages. I also improved the Google Shopping algorithm by evaluating 2M+ products daily to adjust the maximum budget according to the devices used, thus boosting growth and customer acquisition. The impact on ManoMano's growth was considerable.
  • •I developed predictive time series models using LightGBM, validated and adjusted these models to ensure their accuracy and relevance. Then, I integrated the predictive models into marketing processes to improve overall performance. I also rewrote the entire feature calculation algorithm, allowing for scalability and calculating over 500 features on a volume of 1 billion rows.
  • •I measured the actual effectiveness of the models using AB tests, and collaborated with business teams to ensure project success. I also participated in Data Science competitions to refine and improve my skills.
  • •In addition, I maintained the Data Science team's infrastructure, helped push the team's models into production, and provided ongoing support to business teams on their challenges, through analysis or simply feedback I had to give them.
  • •I conducted an in-depth analysis of delivery time estimates at ManoMano, discovering that they were too pessimistic compared to actual delivery times. By recommending the use of tracking data for delivery time calculations, I contributed to a 3% increase in the overall conversion rate.