Habib Hili

The University of Lille is a leading academic institution in France, providing high-quality education across various fields. As a part-time Data Analyst Instructor, I had the opportunity to teach courses on select Saturdays throughout each semester, focusing on building analytical skills in future professionals. Quantitative Communication (Final-year Master’s students in CEPE, approx. 20 students): • Trained students in Microsoft Power BI for creating interactive dashboards and data visualizations. • Demonstrated the importance of visual communication in data-driven decision-making. • Designed course materials to illustrate the impact of data visualization in professional contexts. Econometrics (Final-year Bachelor’s students in Economics and Management, approx. 30 students): • Utilized Gretl and Microsoft Excel to teach economic data analysis. • Led case studies enabling students to apply theoretical concepts in practical scenarios. This experience strengthened my ability to convey analytical skills and contributed to the professional growth of students in quantitative communication and econometrics.

Thales is a global leader in high technology, investing in digital innovation and Deep Tech (connectivity, Big Data, artificial intelligence, cybersecurity, and quantum technologies) to build a secure future. As a Data Analyst with responsibilities as a Data Quality Manager Consultant, I contributed to the creation, loading, and enhancement of an internal database while ensuring data quality. Key Achievements: • Data Loading: Imported and integrated data from various information systems (HR, HSE, Real Estate, Finance, IT, Legal), ensuring data availability and integrity. Used Microsoft SQL Server Management Studio (SSMS) and SQL scripts to integrate data into Microsoft Azure SQL Databases. Leveraged Transact-SQL (T-SQL) scriptsfor ETL processes to manage specific imports and ensure data transformation aligned with business needs. • Business Views Creation: Designed optimized SQL views to meet specific business requirements, facilitating efficient data consultation and analysis. • Technical Support: Assisted in the installation and configuration of databases in a test environment, ensuring a smooth deployment process. • Data Cleansing Strategy: Defined deduplication rules and criteria to correct inconsistencies, with comprehensive documentation to ensure traceability and compliance. This experience strengthened my expertise in data analysis and data quality management. I collaborated with cross-functional teams (HR, Finance, IT, Real Estate) to define requirements and deliver a database that met business standards.

Oney is a financial services company and a member of Groupe BPCE, one of the largest banking groups in France. Specializing in financing and payment solutions, Oney serves both individuals and businesses. With an international presence, it offers credit, insurance, and payment services. As a Data Analyst within the Risk and Data departments, I worked in a team of four (two analysts, a project manager consultant, and a technical manager). My responsibilities included managing the eFront (Aladdin, BlackRock) platform and conducting data analysis for compliance, internal control, and operational risk teams. Key Responsibilities: • eFront Administration: Managed entities, profiles, users, and groups for over 700 users across 10 countries. Ensured secure and tailored access for all users. • Data Extraction: Extracted data for various departments, focusing on consistency and quality. • Analysis and Reporting: Conducted analyses for different teams and developed customized KPI reports to support decision-making. • Technical Support and Training: Provided user support and conducted training sessions to ensure optimal use of the platform. • Project Development and Management: Integrated new functionalities, optimized performance, and customized the user interface with both back-end and front-end enhancements to meet business needs. Technical Environment: • Front Script: Developed scripts to automate processes. • SQL: Used SQL queries for data extraction and manipulation. • Microsoft Power BI: Created interactive reports and dashboards for data visualization. • Python: Developed ETL scripts (extraction, transformation, loading of data). • Snowflake: Managed cloud storage and data processing.

Banque Populaire, a member of Groupe BPCE, is a major player in retail banking in France, providing credit, savings, insurance, and financial services to individuals, professionals, and businesses. As a Data Analyst within the Marketing and Distribution team (comprising four data analysts and a manager), I worked on customer and prospect targeting and segmentation. I also participated in managing commercial and regulatory campaigns across the Hauts-de-France region. We collaborated closely with teams focused on individual clients, professionals, private banking, and insurance. Key Responsibilities: • Customer Relationship Management (CRM) with Adobe Campaign: Designed and deployed commercial and regulatory campaigns across multiple channels, including email, SMS, mail, and mobile applications. • Portfolio Enrichment: Supplied advisors with targeted client segments to help them meet their objectives. • Statistical and Marketing Analysis with SAS and SQL: Created targeting and segmentation models for personalized campaigns. Monitored and analyzed commercial and regulatory activities through detailed statistical studies. • Reporting and Data Visualization with Microsoft Excel and PowerPoint: Updated and created reports to track performance and developed tailored reports to provide strategic insights. • Technical Support for Banking Agencies: Provided assistance in CRM usage to ensure smooth campaign execution. This experience strengthened my skills in data analysis and CRM management. I contributed to the company’s strategic growth and supported the achievement of commercial and regulatory goals.

Cofidis, a subsidiary of Groupe Crédit Mutuel, is a European company specializing in consumer credit and financing solutions. It stands out for its fully remote approach. As a Statistician Engineer (Data Analyst) within the Finance, Risk, and Acceptance department, I worked in a team of 10 (6 data analysts, a project manager, 2 consultants, and a manager). I contributed to developing and deploying machine learning solutions to predict payment defaults and optimize resource allocation. Key Responsibilities: • Machine Learning Algorithm Development with SAS: Developed machine learning algorithms to predict payment defaults, aiming to improve forecast accuracy and manage defaults efficiently by assigning sufficient personnel resources. • Database Management and Anomaly Detection with SQL: ◦ Managed relational databases to ensure data integrity and availability. ◦ Created automated scripts to detect anomalies and proactively correct data, reducing processing errors and enhancing forecast reliability. • Reporting and Data Visualization: Designed and updated dashboards and distributed them to business teams to support data-driven decision-making. This experience strengthened my skills in machine learning and database management, with a direct impact on financial risk management and operational efficiency at Cofidis. By predicting potential defaults, risk costs were better controlled, enabling the company to anticipate and reduce client defaults. Additionally, this approach optimized staff management by adjusting personnel according to periods and specific needs, ensuring optimal responsiveness to efficiently manage activities.