My professional journey has been marked by significant accomplishments that showcase my expertise. I held the role of Delivery Lead at Arundo Analytics, leading cross-functional teams comprising data scientists, solution architects, software engineers, and field engineers. In this capacity, I successfully orchestrated the scoping, development, and operationalization of cutting-edge machine learning and analytical SaaS solutions. This led to tangible improvements in operational efficiency and enhanced decision-making processes.

Prior to Arundo Analytics, I served as a Data Scientist Specialist in the Business Development division of QRI, a prominent Oil and Gas value creation company. My contributions to big data analytics, machine learning projects, economic modeling, and risk assessment positively impacted both National Oil Companies and Asset Management Firms. These initiatives resulted in optimized strategies, reduced risk exposure, and improved financial outcomes.

During my tenure as a Quantitative Advisor at Pemex, I collaborated closely with the CFO and the Risk Managing Director. Over a decade, I developed sophisticated models to forecast energy prices, tariffs, and the P&L statement, while also evaluating the feasibility of strategic projects. Additionally, I spearheaded a division dedicated to optimizing procurement processes within a key business line, generating substantial cost savings for the company.

My academic background includes a PhD in Mathematics from The Institute for Financial and Actuarial Mathematics at The University of Liverpool. Alongside this, I've pursued studies in Actuarial Sciences, Applied Mathematics, and a Master's in Public Management. My commitment to continuous learning is evident through certifications such as Microsoft Certified Azure Data Scientist, Financial Management (Cornell University), Econometric Modeling (ITAM), and Data Sciences (The Data Incubator). Presently, I am pursuing a Master of Computer Sciences at Georgia Tech to further enrich my skill set.

During my PhD, I conducted research focused on designing financially sustainable pension systems amidst the challenges posed by aging populations. The implications of my work extend to practical applications and policy-making considerations at both national and international levels.

My contributions have consistently translated into measurable outcomes, from optimizing procurement processes to enhancing decision-making through advanced analytics. I am dedicated to ongoing growth and innovation in the realm of data science and quantitative analysis.