Data Analyst
I am seeking a Data Analyst position in any field where I can apply my expertise in SAS, Python, and statistical modeling to analyze, asses and optimize data. With experience in automating reporting systems (50% efficiency gain during my internship and developing predictive models (ARIMA/Random Forest), I aim to contribute to credit scoring, default prediction, and regulatory compliance through rigorous data analysis and visualization (Power BI). My economics background and certification in SAS Base Programming equip me to transform complex datasets into actionable risk insights while ensuring data quality and process efficiency in financial decision-making.
I possess advanced proficiency in key analytical tools including SAS (certified in Base Programming) for statistical modeling and process automation, Python (pandas, NumPy, scikit-learn) for machine learning applications and data processing, and R for econometric analysis. My strong SQL skills enable efficient querying and management of complex financial databases. For data visualization and reporting, I'm skilled in Power BI and advanced Excel (including VBA macros). My professional experience with Salesforce CRM and web scraping techniques further enhances my data collection and customer risk assessment capabilities. This comprehensive technical stack, combined with my risk modeling expertise (credit scoring, ARIMA), allows me to effectively analyze portfolios, assess risks, and automate regulatory reporting processes.
I hold a Master's in Applied Economics with a Data Science specialization, where I developed expertise in statistical modeling (SAS, Python, R) through thesis work comparing ARIMA/Random Forest models and analyzing pay discrimination using econometric techniques. My Bachelor's in Economics from Sorbonne Université included a computer science minor, with projects in Python, VBA, and MySQL, plus ESG investment analysis using Bloomberg Terminal. I complement this with SAS Base Programming certification (2024) and rigorous preparatory coursework in economics/mathematics, forming a strong foundation for credit risk analysis that blends quantitative skills, financial acumen, and research experience in predictive modeling.
French (Mother tongue)
Spanish (Fair)
Arabic (Fair)
English (Fluent)
