Gaougaou Raphaël

Design and development of business-oriented automation solutions for clients losing time on repetitive tasks: manual reporting, outdated dashboards, files scattered across multiple tools, processes relying too heavily on copy-pasting.

My interventions include:

· Automating reports and KPI dashboards (Python, SQL);

· Connecting tools via APIs or no-code workflows (Make, n8n);

· Cleaning, structuring, and quality control of data;

· Targeted AI integration (extraction, classification, report generation), always with human validation;

· Taking over or improving existing scripts, with APIs or simple interfaces if needed (Flask, FastAPI).

These missions are supported by RGAnalyzer, a SaaS I designed and developed, which transforms sales files (CSV/Excel) into ready-to-present business reports: KPIs, charts, data quality checks, PDF/Excel/PowerPoint exports. It illustrates my work method: understanding business needs, ensuring data reliability, automating what needs to be automated, and delivering a simple, robust solution usable by non-technical teams.

Development of prototypes and internal projects around concrete use cases: reporting automation, indicator tracking, file analysis, information extraction from documents, automatic sorting, alerts, report generation, and structuring of recurring processes.

These projects allowed me to work on several reusable components in different business contexts:

· Data processing and structuring with Python;

· Analysis of CSV/Excel files and business exports;

· Creation of actionable indicators and visualizations;

· Automation of repetitive tasks;

· Extraction, sorting, and classification of information from documents or emails;

· Generation of reports, work files, or summaries;

· Inter-tool connection via API, Make, n8n, or custom scripts;

· Occasional integration of AI components for sorting, summarizing, qualifying, or verifying information.

These works served as a basis for more advanced solutions, including RGAnalyzer, as well as various adaptable business workflow prototypes for needs such as: opportunity qualification, administrative tracking, internal purchasing, document filing, reporting, or dossier preparation.

Development of data solutions and predictive models in Python for the analysis and forecasting of climate data within international energy projects.

In-depth work on statistical and time-series modeling to anticipate long-term trends and feed decision-making processes.

Design, maintenance, and improvement of automated processing pipelines (Python, SQL) for the collection, transformation, and validation of data from multiple sources.

Processing large volumes of data, implementing consistency checks, and optimizing processing performance.

Development of internal tools for the analysis and response to international calls for tenders: automated document search, extraction and structuring of technical information from heterogeneous corpora.

Close collaboration with data, business, and technical teams in an international context, with high demands on the quality, traceability, and robustness of deliverables.