• ETL Specialist with a penchant for major Cloud providers (AWS, GCP, Azure).
  Extensive experience in statistical and predictive models (machine learning, deep learning, reinforcement learning).

• Oversees the entirety of a data pipeline project. Collects data from various sources (APIs, big data, scraping). Analyzes and processes data (visualization, data mining, A/B tests, EDA). Builds and maintains a data management infrastructure (SQL, NoSQL). Creates supervised, unsupervised, and deep learning models (CNN, GRU & LSTM, NLP, GAN). Deploys models (Docker, automated deployment, automated data flow scheduling and monitoring).

• Key skills:

  • Recommendation and client advice on best practices for GDPR compliance and the security of user information.
  • Explores, cleans, and interprets complex datasets to extract insights.
  • Advanced mastery of Python for developing statistical models and machine learning algorithms.
  • Creates clear visualizations for effective communication of results to stakeholders.
  • Proactively solves data-related challenges with creative and analytical approaches.
  • Ability to collaborate in a team, communicate with non-specialists, and adapt to project evolutions.

• Organizational and priority management skills, analytical and synthesis aptitude, attention to detail. Good interpersonal skills, listening abilities, and teaching aptitude. Performance, solution, and results-oriented.

Objectives
As a GPT Team Tech Lead at Dev Launchers, I lead a cross-functional team, collaborating with a developer, a UI/UX designer, and a product owner to conceptualize and develop a ChatBot dedicated to onboarding new community members. In this role, I steer the team through weekly briefings, leveraging my expertise in language models and artificial intelligence to guide our project. My responsibilities include preparing datasets for Avatar development and ensuring the successful implementation of a Virtual Assistant with a unique personality, well-versed in the roles of organization members and internal projects.

Key Contributions

• Conducted a thorough analysis of available Open Source Language Model (LLM) options and implemented procedures for fine-tuning and integration with Dev Launchers' resources.
• Provided leadership and motivation to the team, fostering a collaborative and innovative working environment.
• Led code reviews, ensuring code quality, and adhering to best development practices.
• Identified and mitigated technical risks and challenges throughout the project lifecycle.
• Aimed to create a Virtual Assistant capable of detecting code errors and assisting members in improving their coding skills.

Objectives

• Merged and aggregated databases.
• Imported data from diverse sources through scraping and API usage.
• Collected datasets.
• Extracted, statistically analyzed, and visualized data.
• Designed web applications for showcasing information.
• Developed Machine Learning models.
• Gathered requirements, negotiated, and established technical specifications.
• Implemented Docker containers and set up Ubuntu virtual machines.

Public Outcomes

• Horysons : CloudFlare security bypass, data acquisition, Machine Learning consulting.
• Dans Ma Bouteille : Cleaning, transcription, and adaptation of external databases.
• Fractionnal IP : Extraction and statistical analysis of UK trademark data.
• Metaview : Designing an API incorporating Movenet and Mediapipe model.

Guided around twenty students in data-related subjects. Supervised module: Data Essentials.

Welcomed guests. Managed Poker floor, monitored tables, and served as croupier for traditional games.

Designed fiduciary and identity documents, brand seals, and conceptualized Motion Design.

Designed and executed graphics for both print and digital media.

Objectives
Building and maintaining a data management infrastructure. Exploratory and descriptive analysis of data. Predictive analysis of structured and unstructured data using artificial intelligence. Industrialization of a machine learning algorithm and automation of decision-making processes.

Achievements

• Booking: Implemented a data extraction and storage pipeline on S3.
• Speed Dating: Conducted quantitative and qualitative studies on a sample population.
• Predictive Marketing: Predicted sales, conversion rates, and customer clustering.
• Review Classification: Utilized Natural Language Processing (NLP) for automated sentiment analysis.
• Get Around: Developed a predictive dashboard and API for Marketing.
• IMDb Score Predict: Managed data management projects.