Data-driven Marketing Analyst and Web3 Growth Data Analyst specializing in the intersection of off-chain signals (social media, community sentiment, customer experience) and on-chain capital flows. I build analytics systems, dashboards, and predictive models that help marketing, growth, and business development teams identify which narratives, KOLs, and campaigns drive real user deposits, retention, TVL, and wallet activity, not just impressions. Background spans social media intelligence and CX analytics during a platform beta phase, followed by independent on-chain protocol research across L1 and L2 ecosystems including Solana and Ethereum. Proficient in SQL, Python, Dune Analytics, BigQuery, data visualization, and marketing automation. Experienced in cohort analysis, churn prediction, funnel optimization, customer segmentation, and translating complex data into actionable strategy for founders and leadership teams.
Self-employed
Remote
Built and published 4 live Dune Analytics dashboards tracking Solana network health, MEV activity, DeFi intelligence, and Farcaster social-to-on-chain behavior, publicly queryable and referenced by protocol researchers and ecosystem analysts. Conducted independent comparative research crossing GEO (AI search visibility) with on-chain data (DefiLlama, Dune) to evaluate brand awareness, mindshare, and capital retention across Solana and Ethereum DeFi protocols. Designed serverless data automation systems (n8n + BigQuery ML) for churn prediction and marketing KPI monitoring, published as open-source repositories demonstrating end-to-end MLOps without dedicated infrastructure. Published analytical frameworks and research via Paragraph and LinkedIn, establishing public proof-of-work in DeFi analytics, airdrop retention mechanics, MEV volatility analysis, and social-to-capital correlation. Portfolio: dune.com/qvaloo | github.com/Qvaloo0x
Gnomai Labs
Remote
Led social media and community data analysis during the platform's beta phase, structuring qualitative feedback into actionable product insights for the founding team and informing onboarding flow improvements. Built automated CX monitoring workflows (n8n) to detect recurring user friction patterns and surface real-time alerts to decision-makers, reducing manual diagnostic cycles and improving response time. Collaborated directly with founders to validate hypotheses, prioritize the product roadmap, and translate user behavior data into product strategy and feature recommendations.
Cuba
Seventeen years diagnosing complex technical issues and translating them for non-technical users. Extracted recurring operational patterns to improve efficiency and customer satisfaction. This customer-facing foundation directly informs my approach to user behavior analytics and friction-point identification in Web3 products today.
Professional Certificate
In Progress
Técnico
Certificate
EF SET English Certificate — B2 Upper Intermediate
Analytics dashboard tracking Solana AppLayer congestion, MEV extraction patterns, and fee pressure dynamics during high-volatility periods. Measures non-vote success rates, fee spikes vs. base fees, and failure drivers to expose the gap between 'network operational' and 'network works for retail users.' Demonstrates production-grade SQL for large-scale on-chain datasets and protocol-level diagnostics.
Exploratory framework mapping decentralized social engagement against wallet activity to identify which conversations and creator narratives correlate with actual protocol participation and capital flows. Bridges off-chain community signals with on-chain behavior using cohort thinking and cross-domain correlation logic.
Comparative framework analyzing airdrop distribution mechanics and post-drop capital behavior across Ethereum L2s and DeFi protocols (UNI, OP, ARB, LDO, zkSync). Evaluates how vesting and unlock structures affect long-term user retention, TVL stickiness, and protocol health.
Production-grade MLOps pipeline using BigQuery ML and n8n orchestration to predict user churn in Web3 and cloud mining contexts without dedicated server infrastructure. Demonstrates end-to-end predictive analytics, low-code automation architecture, and business logic applied to retention problems.
No-code/low-code automation suite consolidating multi-source marketing data into unified reporting pipelines with built-in analysis and alert generation. Eliminates manual reporting overhead and gives growth teams real-time visibility into campaign performance signals.
Modular n8n workflow architecture for real-time customer experience monitoring, diagnostic logging, and automated publishing. Detects friction signals from fragmented data sources and surfaces them to teams without manual intervention.