Rosalía is a data and analytics leader with a career built at the intersection of business, analytics and decision-making. Her trajectory spans financial analysis, actuarial and statistical work, marketing analytics, FP&A, and, more recently, the leadership of enterprise data, analytics, automation, and AI initiatives within the energy sector. This progression has given her a strong ability to connect analytical depth with practical business impact.

Her work has included leading analytics teams, shaping data science strategy, advancing data governance, driving robotic process automation initiatives and implementing machine learning and statistical solutions to interpret large volumes of data to generate business value. She has a strong track record of designing automated solutions that reduce manual work, improve reporting quality and enable organizations to focus more on analysis, insight generation, and execution.

Rosalía combines technical capability with business judgment and works effectively across both technical and non-technical environments. Her experience in the energy industry has further strengthened her understanding of how data can support operations, planning, governance and strategic decision-making in complex business settings.

She holds an MSc in Data Science from The University of Manchester, where she graduated with Distinction as a Chevening Scholar, and a BBA in International Economics from Texas A&M International University, where she graduated Magna Cum Laude and ranked among the top students in her business school.

Rosalía leads oPHtimize’s operations, with direct responsibility overseeing the Data & AI, Analytics, and BI teams.