Credit insurance business transformation project:- Built and optimized the runtime of a financial risk rating model using R, Python, JavaScript and SQL.- Set up 60+ credit risk and rating models in the client’s new platform.- Translated sophisticated mathematical, statistical and financial formulas into code.- Most of the pipelines involved a combination of Python, R and JavaScript, and I was mainly interacting with SQL data sources.- I was working closely with the client Subject Matter Experts on capturing functional requirements and translating them to data engineering pipelines in code.Predictive modelling project for a hospital using artificial intelligence:- Developed a machine learning model which predicts a few hours in advance whether a sepsis infection would attack premature babies.-Most of the data that I was working with was gathered from patients by using healthsensors and we were processing it across the entire data engineering and modelling lifecycles in our platform.-I was mainly programming in Python, but there were some pipelines that were implemented in R.- Improved model performance with engineering several new features and supported model explainability with calculating SHAP values.

- Churn prediction with different machine learning techniques (classification, clustering and neural networks) to advise the sales team taking retention actions on uncertain clients.- Strong focus on predictive modelling and advanced marketing data analysis with customer segmentation.

- Participating in the Finance Summer Internship program as a member of the Valuation Control department- Supporting my colleagues in the valuation data reporting- Automating the Excel reporting by implementing VBA macros in the files- Analyzing in Bloomberg the available external prices of the financial products offered by different sources

-As a member of the Risk Assurance Services team, I have participated in IT and Business process audit projects of companies from the Financial Services sector (mainly insurance)-My day to day tasks included the analysis of SQL queries, review of business processes and validation of calculations