Research in treasury technology and innovation
Deploying Python-based automation and Machine Learning to modernize liquidity architectures. Moving from static reporting to dynamic, predictive cash management.
Research in Macroeconomic Outlook
Data-driven analysis of the Eurozone and Swiss macroeconomic landscape. Deciphering how interest rate cycles and inflation trends impact the cost of capital.
Research in Financial Markets and Risk Management
Quantitative strategies to manage exposure in FX, Commodities, and Debt Capital Markets. Protecting operating margins through rigorous risk modeling.
About Me: David, Founder and researcher
Headline: Liquidity Corporate Treasury at Ferrovial HQ | CTP | AI Researcher
The Professional Profile: Corporate Treasury professional at Ferrovial HQ, currently optimizing group liquidity structures and minimizing non-operating cash balances. With a foundation built in Global Corporate Banking at Santander, I combine institutional rigor with a quantitative approach to financial risk.
As a Certified Treasury Professional (CTP) and M.Sc. candidate in Artificial Intelligence applied to Finance, I am building Treasync to bridge the gap between traditional Treasury Management and Data Science.
The Person: Driven by discipline—both in the markets and in life. Based in Madrid, with a mindset oriented towards international excellence. When I’m not modeling risk or coding in Python, you will find me lowering my handicap on the golf course, skiing the Pyrenees, or touring on my motorcycle
