Martin A. NASSE

• Delivered a training module on real-time data analysis using Python and PySpark, tailored for engineering students • Supervised student projects using open data, with a focus on practical, socially relevant use cases • Provided guidance on designing and implementing data pipelines on cloud based platforms

• Analysed customer behaviour and sentiment to support decision making and improve user experience • Designed and deployed APIs • Built a natural language processing tool to extract insights from call transcripts for senior management • Collect automatically business information from several web pages • Analysis of external data to enrich customer profile or to train Machine Learning algorithms • Automatic content classification • Speech recognition from audio data • Extraction of business information (future projects, hobbies, user interest, reminder dates) from conversation data • Management and supervision of two interns

- Collaborated with international AXA entities (Germany, Italy, Colombia, etc.) to model and analyze the financial impact of natural catastrophes, including extreme weather and climate-related events. - Supervised an intern specializing in Machine Learning and Computer Vision, providing guidance on research and implementation. - Led a project focused on image recognition, involving Deep Learning, data extraction, and exploratory analysis. - Conducted data mining across AXA Group datasets to uncover insights and support strategic decision-making. - Partnered with global AXA teams to compute and analyze results under the Solvency II standard formula framework. - Assessed the statistical impact of natural disasters on capital and risk exposure. - Developed a real-time geospatial dashboard to monitor key capital indicators and portfolio risk metrics. - Delivered forward-looking risk analyses for the Group Risk Department in close collaboration with international stakeholders.

- Development of machine learning algorithms for credit acceptance (support vector machines, random forest, lasso penalization, …) - Assessment of the predictive power of unstructured data through text mining techniques - Use of external data (data coming from other financial institutions) for credit acceptance - Participation in workshops: + Big Data for collection and litigation + Big Data and young customers

Modelled customer churn using logistic regression and advanced segmentation techniques • Automated reporting workflows by migrating existing processes from SAS to R • Analysed contractual indicators and delivered regular monitoring reports to business teams

- Designed and implemented pricing indices to support retrospective and prospective claims analysis. - Conducted correlation studies and developed weighting schemes to enhance pricing accuracy. - Applied dimensionality reduction techniques, including Principal Component Regression (PCR) and Partial - Least Squares (PLS) regression, to improve model interpretability and performance. - Performed segmented analysis of pricing indices to identify trends and anomalies across different portfolios. - Leveraged SAS and SQL programming to extract, process, and analyze large-scale insurance datasets.

Contributed to geomarketing studies, including spatial analysis and market segmentation. Designed and conducted customer satisfaction surveys to gather actionable insights. Performed data analysis to support strategic decision-making and operational improvements. Automated dashboards and reporting tools using VBA programming to streamline data visualization and performance tracking.