walid ziyate

Member of the Performance Solutions team, delivering data solutions for portfolio performance and attribution tools used by analysts, portfolio managers, and reporting officers. • Lead the migration of databases from Sybase to SQL Server, improving system stability and maintainability • Develop advanced SQL Server components such as stored procedures, functions, and views to support complex performance attribution logic • Design and maintain ETL/ELT pipelines in Python and SQL for automating ingestion and transformation of financial datasets • Enhance application performance through database optimization, indexing strategies, and efficient query design • Provide technical support and manage incident resolution to ensure continuity and availability of business-critical applications • Create detailed technical documentation and contribute to knowledge transfer within the team • Collaborate with quants, analysts, and reporting teams to align technical solutions with business requirements Stack: SQL Server, T-SQL, Python, Sybase, VB.NET, Git, Azure DevOps CICD, SFTP, REST APIs, DataBricks

SLAM is a Paris-based asset manager specialized in marketplace lending across the US and Europe, with expertise in BNPL, RBF, and fintech-originated loans. • Interact with internal teams (Front Office, Middle Office, Sales) to gather business needs and translate them into data workflows • Coordinate with external partners (Fintechs, Banks, Depositories, Asset Servicers) to implement and monitor automated data transfers • Collect and consolidate multi-source data via API, SFTP, and scraping, and store it in the enterprise Data Lake • Create and manage Data Warehouse structures to organize and normalize data from platforms, banks, and custodians • Develop, automate, and maintain end-to-end data pipelines in Python and SQL for operational and analytical processes • Build and maintain applications for cash monitoring and reconciliation using SQL, VBA • Implement audit mechanisms to monitor data integrity, detect anomalies, and ensure consistent data quality • Investigate data discrepancies, perform root cause analysis, and propose sustainable solutions • Create dashboards and visual reports to monitor platform KPIs and portfolio performance using SSRS • Provide applicative support, prioritize and resolve incidents, and ensure continuous operation of data processes • Prepare technical documentation covering codebases, workflows, testing procedures, and operational guidelines Stack: Python, SQL, T-SQL, SSMS, Power BI, Excel, VBA, VS Code, Git, Bash Linux, FTP, SFTP, API

Contribute to improving customer satisfaction during technician interventions. • Gather requirements by engaging with business stakeholders to define project goals • Communicate with cross-functional teams to align data needs and expectations • Collect and clean data from customer satisfaction surveys and technician intervention logs • Conduct analysis using statistical tests to identify satisfaction patterns and trends • Leverage Python libraries (scikit-learn, TensorFlow, Pandas, NumPy, matplotlib, seaborn) for data modeling and visualization • Develop and evaluate machine learning models (Random Forest, XGBoost) to predict satisfaction drivers • Create reports and dashboards to present insights and recommendations to management Stack: Python, Jupyter, RStudio, MySQL, scikit-learn, TensorFlow, Pandas, NumPy, matplotlib, seaborn, Excel, PowerPoint, Agile Kanban