About / Approach
Curious by nature.
Analytical by training.
I work where data meets decisions. My background in mathematical engineering and applied data science has taken me from financial risk research and impact investing to building operational tools for underground mining.
I’m interested in turning technical depth into something people can actually use: a model that answers a meaningful question, a clear view of complex data, or a product that helps a team make a better decision.
Toolbox
01
Data science & modelling
02
Engineering & data
03
Finance & analytics
Languages
Education
MSc in Applied Data Science for Banking and Finance
Università Cattolica del Sacro Cuore
Oct 2023 — Sep 2025Thesis: Modeling systemic risk with ΔCoVaR: a comparison of linear and neural network approaches.
Selected project: Benchmark-neutral portfolio optimisation: implemented a custom factor model in Python with targeted factor tilts.
Coursework: Data Analysis, IT Coding, Finance and Banking, Business Analytics, Game Theory, AI and Machine Learning, Data Analytics for Investment, Quantitative Finance, and Time Series Analysis and Forecasting.
Certificate in Finance · Awarded with Distinction
UCLA Extension
Mar 2022 — Dec 2022Coursework: Managerial Finance and Advanced Applications of Managerial Finance, Fundamentals of Investing, Financial Statement Analysis, Principles of Accounting A and B, and Introduction to Data Science.
Bachelor of Science
Politecnico di Milano
Oct 2015 — Jul 2020Final dissertation: Analysed Google’s PageRank algorithm using Markov-chain theory and network analysis to examine the mathematical foundations of webpage importance.
Coursework: Calculus I, II and III, Probability, Statistical Inference I and II, and Numerical Analysis (MATLAB).
In the spirit of collaboration
Let’s make something
useful.
For research, projects, or an interesting problem, the simplest way to reach me is by email.
Email Cecilia Other ways to connect