Eduardo Prieto Valdivieso's Linkedin Analytics

DATA IS POWER. Aeronautical Engineer + Master in Big Data + Master in AI with more than 10 years of experience in corporate and international projects in technological sectors with focus on data. I live in Madrid. PROFESSIONAL INTERESTS SECTORS: Aviation, space, environment, energy, health, public administrations, media, industry, FUNCTIONS: Data Strategy, Data Architecture, Data Governance, Privacy, MLOps, AI, AI Ethics VALUE PROPOSAL -Strategic vision and change management with an incremental and agile approach: process of creating data units from scratch, creation of multinational data driven fintech and definition of Global Data Strategy. -Leadership, effective communication and knowledge management in multidisciplinary, multicultural environments and in front of different audiences: C-Level (CDO, CTO, CISO, COO, etc.) and specialist profiles (DBA, developers, architects, DevOps) in CoViD context (Full remote or hybrid). -Multidisciplinary knowledge (technical and functional) of data architectures and event-oriented solutions, machine learning and AI: cloudification of legacy systems, definition of zero and without previous experience in the organization of cloud platforms and applications of machine Learning and Deep Learning, APIs and microservices, multi-cloud environments, Government model and data quality. - Natural tendency to meet restless people who know how to take risks and are willing to dream in order to grow together. PROFESSIONAL BACKGROUND My value proposition is based on my 9-year experience going through different sectors: aerospace sector, utilities, research, strategic consulting, teaching, industrial sector and banking. I have played many roles as Chief data architect, Business Consultant, Product owner, researcher, Data Scientist Leader. The main functions it has developed are: -Strategic and functional: definition and analysis of strategic scenarios and digital products/use cases, definition of programs and strategic initiatives based on technology, implementation and contingency plans, negotiation and defense of technological proposals, supplier management and risk analysis (operational, technological, security, compliance, ethical, etc.). -Techniques: Python, R and SQL, optimization and training of machine learning/Deep Learning algorithms, BI tools and modeling of SQL and NoSQL databases, deployment of Big Data clusters and cloud stack. -Project management/stakeholders: taking requirements and definition/management of roadmap, backlog, agile teams, budgets, expectations and stakeholders, risks, etc.