Marketing Data Analyst & Performance Marketer · 12+ years in · Madeira, Portugal — working remotely with teams across the world.

Open to Marketing Analytics and Data-Driven / AI-Native Marketing Manager roles, remote.

I spend most of my time turning messy ad and product data into things people actually act on. Attribution models that tell you which channels work. Marketing mix models that size what budget really drives. Dashboards that surface the right metric at the right grain. And, increasingly, the pipelines and bots that turn the analysis into action automatically. I speak English, Russian, and Portuguese fluently, plus intermediate Spanish.

• Attribution & marketing mix modeling (MMM) — channel impact, budget allocation, incrementality
• Analytics engineering — GA4 → BigQuery → dbt → BI, server-side GTM
• Marketing automation & PPC optimization — profit-aware budget and keyword management, human-in-the-loop

• Data & modeling: GA4, BigQuery, server-side GTM, AppsFlyer, Triple Whale
• BI: Looker Studio, Power BI
• Ad platforms: Google Ads, Meta Ads, Yandex Direct
• Automation: Python, n8n, Telegram bots
• Programming languages: SQL, Python, JavaScript

Marketing automation & optimization ⚡ (latest)

• google-ads-budget-bot — margin-aware Google Ads budget optimization from Telegram: weekly audits, profit-based recommendations (break-even ROAS, not vanity ROAS), conversion-lag aware, applied with one tap. Multi-account. Python · Google Ads API.
• google-ads-search-terms-bot — negative-keyword & new-keyword management from Telegram: a deterministic, auditable rules engine (no LLM), human-in-the-loop approval, idempotent writes. Python · Google Ads API.

Analytics & modeling

• ga4-attribution-models — eight attribution models in BigQuery SQL: last-click, first-click, linear, time decay, position-based, last non-direct, data-driven (BQ ML), and a cross-model comparison. Runs on Google's public GA4 sample.
• bigquery-meridian-mmm — marketing mix model using Google's Meridian library. Bayesian inference, full posterior distributions, geo-level support, MCMC diagnostics.
• simple-marketing-mix-model — the OLS + adstock + Hill saturation version, for when full Bayesian is overkill.
• marketing_analytics_sample_reporting — dbt project unifying Facebook, Google, and TikTok ad spend into a clean reporting mart.
• landing-page-ab-testing — SQL templates for AB analysis: frequentist t-test, Bayesian, SRM detection, sample-size calculator, guardrail checks.
• cohort-log-predict — predict day-30, day-90, day-365 retention from just two data points using a power-law fit.

I run portugalevents.eu — a small platform helping local events in Portugal get found. n8n + GA4 + BigQuery + Looker Studio.

Open to AI-Native Marketing Manager / Marketing Data Analytics roles, remote. → LinkedIn

_{marketing analytics · analytics engineering · marketing data analyst · AI-native marketing manager · GA4 · BigQuery · BigQuery ML · dbt · server-side GTM · attribution modeling · marketing mix modeling (MMM) · incrementality · PPC automation · Google Ads API · budget optimization · A/B testing · cohort analysis · retention modeling · Python · SQL · Looker Studio · Power BI · n8n}