Data Scientist

Designed and developed an advanced conversational agent using LLM. Utilized Mistral as the base model, integrating it with the Langchain and DSPy frameworks. This agent includes a categorization and autocorrection layer that ensures response accuracy and has the capability to query an SQL database to retrieve correct numerical information. Supported the Content AI team by performing multiple face-swaps, which were implemented in advertising campaigns based exclusively on AI-generated images, enhancing content personalization and visual impact. Worked on the development of an automatic subtitling system using Fast-Whisper as the main transcription model. Contributed to the creation of simultaneous and multilingual subtitles, improving the accessibility and reach of audiovisual content.

Collaboration with the sales and production teams to define KPIs and key metrics for measuring environmental impact. Performed descriptive and statistical analysis of sustainability data stored in Excel databases from 2019 to 2023. Used data analysis metrics like Power Query to obtain valuable information on the impact of activities on sustainability. Developed 3 interactive dashboards with Power BI to visualize the impact of activities on sustainability in real-time.

Generated 8 million data points using the Runge-Kutta method to analyze the temporal forecast of the Lorenz-94 Chaotic System. Developed and trained a Recurrent Neural Network (RNN) model, specifically an LSTM and a hybrid LSTM, using PyTorch. Achieved a 2.62x improvement in the chaotic system forecast with the hybrid LSTM compared to the standard LSTM.