Amine BIAD

• Established and standardized key performance indicators throughout the organization to optimize the tracking of growth and improve decision-making related to the acquisition of new users.

• Led data analysis efforts that enhanced understanding of new user behaviors using graphical models, resulting in a 9% increase in retention through strategic, data-informed decision-making.

• Developed Python package for A/B test sanity check and analysis, which substantially decreased errors and saved time for team members.

• Improved the efficiency of Logistic Regression bidding models, leading to increase in revenue through the application of advanced machine learning optimization techniques.

• Led R&D efforts for the development of Similarity Search models using the Faiss library, resulting in a new product launch.

• Designed and conducted A/B tests to evaluate both offline and online enhancements in Machine Learning algorithms, delivering essential insights for strategic modifications.

• Managed data pipelines for high-volume user location events, improving data ingestion, transformation, and storage processes.

• Developed predictive models for user demographics and fraud detection, significantly reducing operational costs by identifying and eliminating inefficiencies.

Developed and implemented text summarization techniques using extractive methods and trained Sequence-to-Sequence language models with attention mechanisms, enhancing the summarization of industrial data.