Guillaume Verbiguié

– Identifying and analyzing client needs: Collecting requirements and transforming them into practical use cases with tailored recommendations. – Implementing use cases, ETL processes, and machine learning: Applying ETL techniques and machine learning to solve complex problems using tools such as Invenis, Amadea, and Python for advanced data analysis. – Deliverables creation: Developing dashboards and visualizations using tools like PowerBI, Superset, and DigDash to provide actionable insights for stakeholders. – Strategic support: Advising on Data Strategy, Data Management, Data Governance, and promoting a true Data Culture within organizations. – Cross-team collaboration: Working closely with Sales and Data Science teams to ensure seamless execution of projects, particularly on technical, ETL, and machine learning aspects. – Machine Learning, ETL, and Added Value: By incorporating machine learning and ETL processes, I have automated predictive analyses, streamlined data workflows, and improved project performance while ensuring a no-code approach through our internal software solutions.

Accompanying students on data-related courses (Excel, R, Python, Tableau, and statistical methods such as regressions, PCA, NLP, etc.)

– Data preparation: Data cleaning, scripting, quality and consistency check – Use of various methods of statistical analysis (regressions, PCA, ...) and Data Viz – Management of junior data analysts – Use of processing software such as DAISIE, Power Query/Pivot; programming languages such as Python (in particular Pandas, NumPy, scikit-learn), R, VBA and analytics/data viz software such as Tableau, Power BI, SAS

Attached to the Brand and Digital Department and within the Datamining division: – Implementation of the CRM contact plan on all communication channels (Email, Mail, SMS, Couponing) – Realization of statistical modeling studies to increase customer knowledge and omnicanal vision. – Monitoring of KPIs to manage CRM activity, development of reporting – Participation in transversal projects with the ISD – Campaign management and analysis of campaign results – SAS, SQL, Excel, Teradata, MicroStrategy

Within the Datamining Research department, responsible for the monthly production of commercial scores on all markets. In relation with the different teams (CIO, MOA, Research Managers), I made sure that production ran smoothly: – Compliance of the SAS script, Production start-up, Parameterization of controls, etc. – Launching scores according to a precise process (dependencies, respect of deadlines) – Validation of the quality of the data from the scores – Impact analyses related to data changes or changes to the production plan – Production monitoring (dashboards and monthly reports)

– Implementation of daily/weekly/monthly management tools and ad hoc risk analysis studies – Analysis and redesign of award and pre-targeting scores – Creation of databases and quality control on these databases – SAS Program Optimization – SAS (basic, sql, macro, Enterprise Guide), R, Excel, PowerPoint