Amel Hamzaoui

* Successfully led migration from legacy Oracle systems to modern MongoDB platform, ensuring seamless transition and zero downtime. * Managed full data lifecycle: ingestion, transformation, migration, and publication, improving data reliability and accessibility. * Built and led a high-performing data team, meeting tight deadlines and driving operational excellence. * Chaired Data Board to resolve issues, optimize data workflows, and maintain data quality. * Collaborated with CEO and CTO on strategic data initiatives, driving business value and cultural change. * Automated global data processes via CI/CD pipelines, boosting scalability and efficiency. * Administered MongoDB clusters, enhancing performance through monitoring, scaling, and query optimization.

* Optimized the performance of a large-scale recommendation engine by fine-tuning MongoDB queries, indexing strategies, and data modeling to support high-throughput, low-latency operations. * Designed and implemented comprehensive backup and restoration processes for MongoDB and MySQL clusters, leveraging automation tools such as Ansible, shell scripting, JavaScript, and Dollar Universe to ensure data integrity and disaster recovery readiness. * Developed and maintained automated operational workflows for database maintenance, scaling, and monitoring, improving system reliability and uptime. * Delivered technical coaching and mentorship to Developers and DevOps teams, enhancing their proficiency in MongoDB best practices, cluster management, and performance tuning. * Collaborated with cross-functional teams to integrate big data solutions into existing infrastructure, ensuring smooth deployment and operational consistency.

* Administered and optimized Big Data infrastructure, including Hadoop ecosystem and MongoDB clusters, ensuring efficient data processing and storage. * Developed and executed robust data migration pipelines to seamlessly transfer and transform data from Hadoop to MongoDB for advanced analytics. * Designed, trained, and validated machine learning models using Python and Scikit-learn to uncover patterns and drive predictive insights from large, complex datasets. * Created automated reporting scripts and statistical KPIs, enabling data-driven decision-making across teams. * Built interactive dashboards with Elasticsearch and Kibana, facilitating intuitive data visualization and real-time monitoring of key metrics. * Collaborated with cross-functional teams to translate analytical findings into actionable business strategies, improving customer engagement and product development.

* Developed and implemented advanced machine learning algorithms to analyze fragmented and anonymized datasets, extracting valuable insights despite data limitations. * Leveraged strong programming skills in C++ alongside data mining tools such as Weka to build, train, and validate predictive models tailored to complex and heterogeneous data sources. * Conducted rigorous experimental evaluations to improve model accuracy and robustness, contributing to the advancement of applied machine learning techniques in challenging real-world contexts. * Collaborated with interdisciplinary teams to interpret results and translate research findings into practical knowledge extraction methods.

* Developed a novel clustering algorithm based on the K-Nearest Neighbors shared neighbor approach, advancing state-of-the-art techniques in unsupervised data analysis. * Engineered an image grouping application integrating the new algorithm for the Exalead/Dassault search engine, demonstrating expertise in C++ software development and practical deployment. * Designed and implemented a content-based plant image clustering system tailored for botanical research, combining C++ and Matlab to facilitate efficient categorization and analysis of complex image datasets. * Conducted rigorous experimental evaluation and optimization of clustering methods, contributing to both theoretical insights and applied solutions in the field of pattern recognition. * Published findings in scientific venues and collaborated with interdisciplinary teams to bridge algorithmic research and domain-specific applications.