The Good Data Factory
Achraf Oussidi is a Lead Data Scientist at The Good Data Factory since February 2019, where responsibilities include managing a team, researching and implementing state-of-the-art models, standardizing machine learning algorithms, and overseeing the Data Science Life Cycle. Previously, Achraf worked as a Data Scientist at Publicis COSMOS focusing on affinity and propensity modeling and recommendation engines in April 2020. Before that, Achraf contributed to data science and machine learning efforts for digital marketing at SEPHORA, specializing in customer churn prediction and deep learning-based propensity modeling from April 2019 to February 2020. Achraf holds a Master's degree in Data Science & Big Data from Ecole Nationale Supérieure d'Informatique et d'Analyse des Systèmes (ENSIAS) and a Bachelor's degree in Mathematics and Computer Science from University Jobs.
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The Good Data Factory
In a world drowning in data and starved for information and actionable insight, The Good Data Factory steps in to fill an ever-increasing skills and capability gap. We serve as a strategic data science partner to our clients, from startups to large corporations, either having an in-house team of data analytics or not, and we help them to effectively shape their business strategies and create a sustainable competitive advantage in the digital and experience economy. Our team of Data Engineers and Data Scientists bring a disciplined approach to the treatment of data through out the Data Science pipeline. They ensure data is available in a purpose-fit format and quality at every stage of the Data Science lifecycle without compromising the integrity of the original raw data corpus. Our Data Scientists are Mathematically grounded with PhDs and Post-Doctoral on-going research in Abstract and Applied Mathematics. They are skilled in multiple modeling approaches and capable of understanding a problem domain, characterize its dimensions of complexity, project it into the appropriate solution space to reduce complexity and surface latent or hidden attributes and patterns leading to simpler and better performing algorithm than the usual brute force approach. We are working with clients from varying industries including Retail, Digital Marketing, Banking, Insurance and Energy. Give us your most challenging Data, Analytics or Data Science problem and let us show you a different way at solving it effectively and efficiently.