ÂÜÀòÂÒÂ×

Safa MADIOUNI is an experienced data scientist currently working at Jellysmack since October 2021. Previously, Safa worked as a Deep Learning Engineer at SNCF, focusing on unsupervised deep learning for anomaly detection, and as a Deep Learning Research Engineer at IDEMIA, specializing in lossy portrait image compression and synthetic image generation using generative adversarial networks. Earlier roles included machine learning engineering positions at Orange Tunisie, Ooredoo Tunisie, and BANQUE DE TUNISIE, concentrating on customer churn prediction, identification of interested customers, and solvability prediction. Safa began a career as a Data Analyst at the Institut National de la Statistique, analyzing the effects of oil price fluctuations on economic aggregates. Educational qualifications include a Master’s degree in Statistical and Financial Engineering from Université Paris Dauphine - PSL and an engineering degree in Statistics and Data Analysis from École Supérieure de la Statistique et de l'Analyse de l'Information.