GTM Engineer working at the intersection of B2B sales operations, data engineering, and automation. Based in Barcelona 🇪🇸
I build the systems that turn raw prospect data into actionable outbound pipelines: territory segmentation, contact deduplication, channel routing logic, and weekly campaign delivery. I also apply machine learning to real sales problems, including predictive lead scoring trained on live outbound data.
Pipeline & data engineering Design and automate B2B prospecting pipelines: cleaning and normalizing CRM exports, deduplicating by domain and LinkedIn URL, applying business logic (contact caps, territory assignment, language callability), and generating segmented, channel-ready output files.
GTM systems & campaign operations End-to-end campaign management across 15+ client accounts simultaneously, configuring outreach identities, warmup, sequences, and enrichment workflows in Enginy and Clay. Multi-BDR territory splits, exclusion logic, and weekly prioritization at scale. Clients include enterprise software companies, Microsoft Gold Partners, and global technology vendors.
Applied ML for sales Built a LightGBM lead scoring model on real outbound prospecting data (~6,000 contacts, 14% positive rate). Features include engineered signals from LinkedIn enrichment, K-Means cluster membership, and job title embeddings compressed with UMAP. Evaluated with PR-AUC and Precision@100 due to class imbalance. Achieved 2.6x lift in top 10%, meaning 25 extra sales conversations per week at zero additional cost.
Languages Python
GTM tools Enginy · Clay · Apollo · Prospeo · LinkedIn Sales Navigator
ML LightGBM · XGBoost · scikit-learn · K-Means · UMAP · SHAP · Optuna
Automation Python scripting · Claude Code · API basics
LightGBM classifier trained on real outbound prospecting data from a Microsoft Gold Partner's sales team. Features combine engineered signals from LinkedIn enrichment data, K-Means segmentation, and dimensionality-reduced job title embeddings. SHAP analysis revealed that mid-level decision makers (VPs, Directors) outperform C-level contacts by 2x in response rate, a finding that directly challenged the client's targeting assumptions.
python lightgbm umap shap optuna kmeans sales-ml
Python pipeline that takes raw CRM exports and produces segmented, channel-ready contact lists for a B2B outbound team of 4 BDRs across LATAM, EMEA, Spain, and Italy. Handles territory assignment, buyer/influencer/referrer caps, language-based call routing, 3-month backup reserves, and formatted Excel summaries for weekly briefings.
python pandas b2b-sales gtm data-pipeline
Web scraping pipeline for public procurement data that extracts and structures bid listings for commercial targeting.
python web-scraping b2b-sales
2 years as BDR, then 1 year as GTM Engineer at a B2B sales consultancy managing outbound infrastructure for 15+ simultaneous client accounts across cybersecurity, enterprise software, staff augmentation, HR and e-commerce. MSc in Data Science & AI, Nuclio Digital School.
The combination is unusual: most GTM engineers don't have ML training, and most data scientists have never configured a BDR identity or written a cold outreach sequence. I work in both.
📍 Barcelona, Spain
🎓 MSc Data Science & AI, Nuclio Digital School
💼 GTM Engineer, B2B sales consultancy