Andrea Argudo | Technical Product Manager
Product Owner in financial systems — data platforms driving product & AI
If the problem isn’t defined, you’re just building — with no direction and no impact
What I do when things break
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Cut scope when it doesn’t move the business
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Bring engineering in early — not just to build
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Force clarity before agile delivery (Scrum y Kanban)
What this looks like in practice
Business (Revenue & Efficiency)
↑ Revenue / ROI
↓ Operational costs: ~20%
↑ Avg ticket size: ~13%
Product (Conversion & UX)
↓ Drop-off: 15–25%
↑ Deposits: ~20%
↓ Transaction time: ~30%
System (Reliability & Cost)
0 critical incidents
↓ Infra costs: ~40%
↓ Latency: ~200ms
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Contact: argudoandrea@gmail.com
From B2C to B2B — I don’t work on everything, just what’s broken
B2C — Apps & Web
User acquisition · Conversion · Engagement
B2B / Internal platforms — Systems & Infrastructure
Real-time · Data · Reliability · Cost
Product (Conversion & UX)
↓ Drop-off: 15–25%
↑ Deposits: ~20%
↓ Transaction time: ~30%
Customer jouney Optimization
Real-time Decision System
↓ Critical incidents: 0
↓ Infra costs: 40%
↓ Latency: ~200ms
Centralised to Distributed Real-Time Architecture Migration
Winter Olympic Games 2026
Product (Acquisition & Conversion)
↑ Users acquired: +10K
↓ Drop-off: ~15–20%
↑ Avg ticket size: ~13%
E-money platforms & security
E-money Platform — Multi-party Control
↑ Secure execution of high-value Bitcoin transactions
↓ Risk in multi-party approvals
↓ Costs vs traditional multisig
Product (Engagement & Usage)
↑ Engagement: ~12% (~50K MAU)
↑ Interaction rate: ~20–30%
Prioritized engagement features to increase usage and retention.
GenAI Engagement
Built AWS data & ML platform from scratch
Data Platform (Reporting & ML)
↓ Reporting time: hours → minutes
↑ Data availability: ~24h
ML in production (batch)
Built from scratch to unblock reporting and ML usage.
I fix the bottleneck, not the symptoms.