Daniel Miranda

Leading multiple high-impact initiatives across enterprise monitoring, AI product validation, supply chain innovation, and workflow automation. ENTERPRISE PROCESS MONITORING PLATFORM ($2MM ANNUAL SAVINGS) Led end-to-end product strategy for strategic monitoring platform serving executive stakeholders (VPs/Directors): IMPACT & RESULTS: • Generated estimated $2MM annual savings through 90% improvement in incident response time • Achieved 97% data adherence, enabling more assertive business decisions • Reduced critical data loss from 7-10% to 1% through automated health checks • Improved order management quality by 73% • Drove 70% process maturation across monitored workflows PRODUCT STRATEGY & EXECUTION: • Conducted comprehensive discovery with C-level executives to build roadmap aligning competing priorities • Architected core features including AI predictive analysis and automated runbooks • Implemented iterative methodology with POCs and feedback-based MVPs • Created 40+ process quality indicators in Grafana using advanced PromSQL queries • Solution recognized by executive leadership for high strategic relevance AI PRODUCT MANAGEMENT TOOLS VALIDATION (LOVABLE PLATFORM) Led 3-month initiative to optimize PM tools for 50+ Product Managers at AmBev: VALIDATION PROCESS: • Conducted complete technical validation comparing Lovable vs Replit vs Dyad • Ran 1-month technical testing across all three platforms • Executed practical tests with 15 professionals to validate usability and team fit • Prioritized adaptability for business-oriented PMs vs developer-heavy tools IMPACT & RESULTS: • Reduced screen homologation cycle from 2 months to 2 weeks (75% reduction) • Transformed POC culture: POCs now prepare for v0 rather than being final product • Enabled faster wireframe validation with stakeholders before design system adaptation • Resulted in deliveries with greater maturity and adaptability INNOVATION LEADERSHIP & MENTORING (SUPPLY CHAIN) Mentored Junior PM for 7 months on supply chain innovation products: METHODOLOGY: • Transformed business needs into algorithms through agile validation • Established Python POC → C#/.NET production pipeline • Implemented iterative process for quick business logic validation IMPACT & RESULTS: • Validated 4 POCs with 95% code reuse rate • Reduced analysts' manual work from 1h30min to 10-15min (83% reduction) • Decreased manual adjustment error rate from 30% to ~5% • Generated estimated savings of R$5MM ($1MM USD) • Accelerated time-to-value and reduced development risks MCP DEVELOPMENT FOR PROCESS AUTOMATION Developed 2 custom MCPs (Model Context Protocol) for workflow automation: MCP #1 - TASK ESTIMATION & SCHEDULING: • Based on company's work model integrated with corporate calendar • Automatically generates implementation dates with 100% accuracy • Deviations only related to unforeseen development issues • Adopted by 23+ professionals MCP #2 - AZURE DEVOPS TASK CREATION: • AI agent follows company standard process automatically • Reduced documentation effort from 40min to 8min (80% reduction) • Streamlined task creation and registration workflow • Adopted across product management teams TECHNOLOGIES: Grafana, PromSQL, Datadog, Prometheus, Python, C#/.NET, Azure DevOps, Lovable, MCPs, AI-powered development tools

Led complete digital business model implementation and production pipeline in traditional publishing house accustomed to producing physical books. DIGITAL BUSINESS MODEL IMPLEMENTATION TRANSFORMATION STRATEGY: • Transformed physical book production pipeline into digital-first model • Converted editors into effective Product Managers through comprehensive training program • Implemented Agile methodologies and digital product management tools • Conducted needs assessment to identify team challenges PROCESS OPTIMIZATION: • Defined clear roles and responsibilities across teams • Implemented standardized processes (user flows, wireframes) • Cultivated digital product culture empowering editors for PM functions IMPACT & RESULTS: • Improved time-to-market by 30% • Increased customer satisfaction by 25% (measured by NPS) • Optimized complementary digital product development workflow AI AGENT FOR CONTENT DELIVERY (COPILOT) IMPLEMENTATION: • Identified and analyzed content delivery process inefficiencies • Built custom AI solution using Microsoft Copilot • Integrated with existing content management systems IMPACT & RESULTS: • Optimized content delivery processes by 80% • Achieved 98% accuracy in automated content processing • Eliminated critical operational bottleneck • Enabled scaling of content operations TECHNOLOGIES: Microsoft Copilot, AI automation, content management systems, Agile methodologies

Led development of AI-driven products and enterprise system optimization for clients in the financial sector. OPEN FINANCE LLM - TRANSACTION INTELLIGENCE PLATFORM (MASTERCARD) Led development of Large Language Model as core component of Mastercard's Open Finance strategy across Latin America: PRODUCT VISION & STRATEGY: • Enabled financial institutions to deliver enriched transaction data to end consumers • Ensured compliance with regional Open Banking regulations • Transformed unstructured banking data into actionable financial insights TECHNICAL EXECUTION: • Conducted deep analysis of Brazilian financial data patterns • Built logical workflow for model training and data enrichment • Designed scalable and modular solution architecture • Improved model accuracy from 74% to 97% (exceeding 92% target) CROSS-BORDER EXPANSION: • Solution successfully adopted in United Kingdom market • Expanded to Australia market • Demonstrated deep understanding of regulatory compliance across jurisdictions COMPLIANCE & RISK MANAGEMENT: • Collaborated with Legal, Compliance, and Risk teams • Ensured product met Open Finance regulatory requirements: - Data privacy compliance (LGPD in Brazil) - Consumer consent management - Financial data standardization mandates • Navigated complex regulatory landscape across multiple countries IMPACT: • Directly enabled Mastercard's Open Finance expansion in Latin America • Delivered compliant, high-quality data enrichment services • Scaled across payment networks in Brazil, UK, and Australia • Set foundation for future market expansions EMPLOYEE EVALUATION SYSTEM OPTIMIZATION (BV) Redesigned employee evaluation system addressing critical UX issues: PROBLEM IDENTIFICATION: • System featured lengthy, complex questionnaires • Excessive evaluation times (50-55 minutes) • Low user satisfaction from project managers DISCOVERY & RESEARCH: • Conducted in-depth interviews with project managers • Analyzed complete user journey to identify bottlenecks • Mapped specific needs and pain points SOLUTION DESIGN: • Simplified questionnaire language and structure • Focused on critical evaluation criteria • Streamlined evaluation workflow IMPACT & RESULTS: • Reduced average evaluation time by 70% (from 50-55min to 15-20min) • Significantly increased manager satisfaction • Improved evaluation completion rates and data quality TECHNOLOGIES: LLM training & fine-tuning, Open Finance APIs, Compliance frameworks, User research methodologies, Journey mapping

Bootcamp in cui sono stati sviluppati progetti reali per risolvere problemi concreti di aziende partner. I progetti includevano strumenti cloud di Google e tutte le sue altre strumenti interni, come BigQuery, Looker, creazione di VM per ospitare pagine web, applicazioni in container con Cloud Run, registrazione di API in container, esecuzione di build e altro ancora. Sono stati utilizzati i linguaggi Python e SQL, e sono state sviluppate anche competenze di gestione dei progetti. La gestione dei team è stata applicata e praticata guidando team di fino a 7 persone per consegnare e validare i prodotti e le soluzioni implementate.