Pedro Alizo
Finance systems operator · Forward Deployed Engineer track
Madrid · English & Spanish · 15 years finance systems
Career focus
Forward Deployed Engineer · Applied AI
I turn finance workflows into controlled, inspectable software: definitions, ownership, and review paths first; narrow prototypes second. Public technical evidence is prototype-stage and deliberately scoped—not a claim of production AI deployment or external customer outcomes.
- Operating context
- 15 years in studio finance, FP&A, reporting, and systems change across the US, Latin America, and EMEA.
- Systems change
- Regional finance-team leadership and SAP implementation experience across Latin America.
- Hands-on work
- Python, SQL, and synthetic-data review workflows with visible calculations and human review controls.
- Evidence boundary
- No production AI deployment or external customer outcome is claimed.
Work samples
View all-
Plan-to-actual exception triage with synthetic data, source references, and human review controls—what a 30-minute hiring review should inspect.
Status: Interactive prototype
- Calculates variance amount, percentage, and direction, with explicit handling when the plan baseline is zero.
- Lets a reviewer mark a synthetic exception reviewed or escalated; decisions remain in browser memory and are not written back.
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Deterministic statement ratios, formula traces, and missing-data states on synthetic scenarios—built for a focused hiring-screen walkthrough.
Status: Static browser prototype
- Calculates revenue change, margins, liquidity, and working capital from visible synthetic inputs.
- Leaves comparisons unavailable when the prior period or a valid denominator is missing.
Featured writing
View all- What a LatAm SAP Cutover Taught Me About Finance Systems
Experience-labeled lessons from leading regional finance teams through an SAP implementation across Latin America: ownership, cutover readiness, and controls that match how teams close.
Oct 17, 2026
7 min
- Why the Statement Workbench Is Static on Purpose
A Cloudflare Pages–compatible finance review prototype stays browser-only: deterministic TypeScript, synthetic fixtures, and no model calls—so the control boundary stays inspectable.
Oct 17, 2026
5 min
- Embedded AI, Point Solution, or Neither?
A practical framework for deciding how to govern AI features in existing software, dedicated tools, and internal builds.
Sep 1, 2026
7 min
- Data Lineage Is a Practical AI Bottleneck
AI-generated finance answers inherit ambiguity in source data, metric definitions, and ownership. Data lineage makes those dependencies reviewable.
Aug 18, 2026
6 min
- How to Measure AI ROI in Finance Pilots
Set a baseline, track workflow adoption, and separate time saved from quality improvements when evaluating an AI pilot.
Jul 21, 2026
6 min
- Adapting Model Risk Policy for Language Models
Most finance orgs still govern AI tools using a model risk framework built for regression models and rate curves. That framework doesn't ask the right questions about an LLM. Here's what to add, not throw out.
Jul 14, 2026
8 min
Tie-Out
Occasional notes on controls, economics, and judgment in corporate finance. No fixed cadence.
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