Andrey Ramirez Ospina

I designed and implemented a microservices-based ecosystem to automate digital supervision, integrating regulatory validations, predictive analytics, and dynamic data visualization. A 30% improvement in the scalability and availability of the solution was achieved.

I led the implementation of a comprehensive cybersecurity framework, adopting standards like ISO 27001, OWASP Top 10, and NIST 800-53, with secure CI/CD practices. Achieved a reduction of over 60% in regulatory compliance errors.

I executed a complete migration strategy to cloud-native infrastructure on AWS, optimizing resources with containers and CI/CD automation. This resulted in a 35% reduction in operational costs and improved resilience for regulated environments.

I designed and implemented a business continuity plan (BCP) and disaster recovery plan (DRP) for critical SaaS solutions. This ensured zero data loss and an optimized RTO/RPO, strengthening operational reliability against disruptive events.

I designed and integrated an explanatory AI module based on large language models (LLM) to interpret complex financial variables and generate automatic explanations for financial and executive users. This system empowers leaders by transforming raw data into clear, actionable narratives, thus democratizing financial understanding across the organization. Its implementation was a milestone in financial innovation, not only by optimizing analysis times but also by promoting a data-driven culture based on transparency and accessibility. This initiative not only democratized financial understanding but also became a strategic pillar, providing a solid, data-driven foundation for decision-making at all levels.

Key features:

A 45% improvement in the understanding of results and a reduction in the analysis time of regulatory financial reports were achieved.

I implemented a predictive modeling solution that combines internal variables (operational and financial KPIs) with exogenous sources (inflation, rates, country risk, etc.) to generate simulated scenarios and early warnings. Using supervised machine learning models and cross-validation techniques, it was possible to:

This proactive approach not only mitigates risks but also uncovers hidden opportunities, enabling more agile and well-founded financial management. This tool became a strategic ally for senior management, providing a quantitative and forward-looking view to navigate market uncertainty. Early response capacity to critical environmental conditions was increased by 60%.