I build the operating systems behind growth: the processes, software and management decisions that turn ambiguous work into accountable numbers.
01 / About
Based in Brazil. Working across operations, technology and capital allocation.
Over six years I delivered systems for more than 60 clients in Brazil, the United States and Europe. I later grew a side project into AlturionX, a B2B operation with 16 paying customers and $47K ARR, then sold the platform and client book.
I lead with numbers, but not theatre. I can review the unit economics with a client, rebuild the process with the team and write the automation when that is the shortest path to a better outcome.
Selected outcomes
$47K
ARR built before exit
16
paying B2B customers
74%
reduction in cost per lead
2.3×
increase in customer LTV
60+
client engagements delivered
42%
productivity gain at Cliniq
02 / Experience
2024—2026
AlturionX
Grew the 2023 SkytOffer side project into a B2B operations product. Led eight people across engineering, commercial and delivery; owned architecture, customer economics and the monthly results conversation. Reduced average cost per lead by 74%, increased LTV by up to 2.3× and completed a four-week acquisition handover with zero customer churn.
2020—2024
Independent
Delivered production systems and operational automations for more than 60 clients, often entering existing teams where the real problem had been misdiagnosed as a software request.
03 / Selected work
Management information
↗+42% team productivity
Built a Python and BI operating dashboard that consolidated fragmented indicators into one management view, giving the team a clearer daily cadence and faster decisions.
Process automation
↗2 days → under 1 hour
Rebuilt a slow administrative workflow as Node.js services on AWS, automating the repetitive stages while keeping human approvals visible and controlled.
Commercial analytics
↗5× faster reporting · +34% ROAS
Created a Python analytics pipeline over campaign data. Faster reporting made segment economics visible and the resulting analysis contributed to a 34% increase in return on ad spend.
Investment decision support
↗Deterministic decision system
Translated investment criteria into a deterministic Python system, making recommendations reproducible, auditable and less dependent on spreadsheet interpretation.
04 / Leadership
A call that worked
A major account asked for a WhatsApp bot. Their larger problem was that 60% of inbound demand was unqualified, so I put lead scoring first. Cost per lead fell from $41 to $11. We still shipped the auto-responder later—because their team was working at 11 p.m., a problem the metric alone did not reveal.
A call I corrected
I chose a single-tenant schema for the first six customers because it was faster in month one. At customer seven, it cost roughly three weeks to unwind. The lesson was not “always design for scale”; it was to name the threshold that would force a redesign before speed became structural debt.
05 / Capabilities
01
Turning loose routines into measurable processes, ownership and management cadence.
02
Connecting product and operating decisions to acquisition cost, retention and revenue.
03
Excel, BI, Python and software automations that remove manual work without hiding controls.
04
Making architecture, buy-versus-build and risk decisions in language the business can use.
05
Managing expectations, presenting results directly and fixing what changes the outcome.
06
Aligning engineering, commercial and delivery work around a small set of accountable numbers.
Technical depth
Code is not the headline. It is how I shorten the distance between a management decision and a working system.
Education
Economics · PUCPR
2020—2023
Machine Learning & AI with Python · Harvard Online
2025—2026
AI: Implications for Business Strategy · MIT Sloan
2024—2025
Entrepreneurship & Go-to-Market · Harvard / G4
Executive education