I'm at my best when there's a messy, manual process and someone needs to turn it into something reliable. I can sit with the ops team, understand how the work actually gets done, and then build the tool that fixes it, whether that's an AI automation, a data pipeline or a dashboard.
Three strengths stand out:
Building practical AI tools. I've designed AI workflows that real teams use daily, with validation built in so people can trust the output.
Questioning the data. I don't take numbers at face value. At an Australian AdTech scaleup in out-of-home advertising measurement, I traced a reported volume spike back to a data coverage issue before it misled leadership.
Bridging tech and business. I translate between engineers and non-technical stakeholders, and I can own a project end to end without needing much hand-holding.
I’m fairly open, but I’m not looking for roles that are mainly data entry or manual reporting with no room to build or automate, or purely sales-focused positions. I’d also prefer to avoid unpaid or equity-only arrangements for full-time work.
I’m bilingual in English and Spanish, and my background spans engineering, supply chain and data, so I’m comfortable working across very different teams and problems.
Right now I’m building an AI project based on my engineering thesis on logistics costing, and studying for the Microsoft PL-300 Power BI certification.
I’m based in Sydney and available to start immediately.
At an Australian AdTech scaleup specialising in out-of-home advertising measurement, the ops team was converting client Insertion Orders into Booking Forms by hand. Each one took 45 to 120 minutes, across roughly 8 campaigns per person a day, and errors in dates, supplier codes and formats kept slipping through.
I rebuilt the process using AI. I mapped every business rule, then built two Gemini Gems to handle the conversion and creative allocation, plus a Claude Skill backed by a Python script for the wider team. The part I'm most proud of is how I handled trust: instead of letting the AI silently guess, every output was tagged as AUTO, INFERRED or NEEDS_REVIEW, so the team knew exactly what to check. A partial booking form with clear flags beats a complete one with hidden errors.
Processing dropped to around 25 minutes per campaign, saving 100+ person-hours a week, and the tool was rolled out to the ops team in the Philippines. Internally it was seen as a game changer, and it opened up the conversation about what AI could actually do for the business beyond just this one process. It showed me that the hard part of applied AI isn't getting the model to produce an answer, it's designing the system so people can rely on it. That's the kind of work I want to keep doing.
Data Analyst and IT & Data Support Engineer with 3 years of experience across AdTech, SaaS, and operations environments. Skilled in SQL, Python, AWS, and AI-powered tooling. Open to Data Analyst, Analytics Engineer, BI Analyst, and Insights Analyst roles.
Core competencies:
SQL query development and database auditing (Metabase, PostgreSQL)
ETL pipeline support and data quality investigation
Python scripting for data cleaning, analysis, and automation
AWS Cloud (Certified Cloud Practitioner + AI Practitioner)
Business Intelligence and stakeholder reporting
Prompt engineering and AI-assisted workflow automation (Claude, Anthropic)
Campaign data analysis in Out-of-Home (OOH) advertising
Cross-functional communication between Engineering and non-technical teams
Industries:
AdTech, OOH Advertising Measurement, SaaS, Operations, Supply Chain
Master of Data Science
Western Sydney University • 2022 – 2024
Bachelor of Industrial Engineering
Universidad Distrital Francisco José de Caldas, Bogotá • 2009 – 2015
Advanced Diploma of Project Management
Academies Australasia, Sydney • 2017 – 2018
Professional Year Program
Performance Education, Sydney • 2025 – 2026
Certifications
