I'm Nikita, a Full Stack Developer from Spain. I build products end to end: the backend, the frontend, and the servers they run on.
My recent work is mostly Rust (Axum, Leptos, Yew), Python and Node.js. I deploy on my own Hetzner VPS running k3s, Docker and Terraform, behind Cloudflare. Before that I spent two internships building on Odoo. In 2026 I finished a 320-hour Data Science & Machine Learning bootcamp.
- 💼 Now: Software Developer at Apartamentos Sierra Nevada
- ⚡ Building: RecoilApp, real-time messaging infrastructure
- 🏢 Running: NieveSoft, a custom software engineering studio
- 🎓 Certified: Data Science & Machine Learning, 4Geeks Academy (320 h, 2026)
- 🌍 Languages: Spanish · English
- ☕ Fun fact: deep aversion to paywalls, deep love for coffee
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Real-time messaging platform with servers, channels, threads, voice/video calls and bots.
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My portfolio, styled as a terminal. It is also where I test new infrastructure ideas.
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All-in-one app for freelancers: clients, jobs, time tracking and invoicing. Private project, in daily use.
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Website for my software studio, written entirely in Rust with no npm.
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| Period | Company | What I did |
|---|---|---|
| Dec 2025 – Present | Apartamentos Sierra Nevada | Cut data-loss risk by 80% with a backup system that keeps five redundant copies. Raised error detection by 90% with custom monitoring across three servers. |
| Nov 2025 – Mar 2026 | Avisur Desinfecciones | Designed and built AvisurCRM to replace the legacy CRM, and migrated its data. Automated questionnaires and document generation. Ran the Linux production servers. |
| Jan 2022 – Feb 2026 | Money Consulting | Built analytics dashboards for investment decisions. Made data loading 30% faster. |
| Mar 2025 – Jul 2025 | Nanobytes (Odoo Gold Partner) | Customised Odoo views, workflows and QWeb reports. Migrated client data with ORM scripts. Resolved production incidents. |
| Mar 2024 – Jul 2024 | TREY Kilobytes de Soluciones | Extended production Odoo modules. Built invoicing and inventory report templates. |
📊 Data Science & ML projects (4Geeks Academy bootcamp)
| Project | Topic |
|---|---|
| image_classifier | Dogs vs cats classification with a VGG16 CNN |
| linear_progression | Medical insurance cost prediction |
| regularized_linear_regression | US county-level health data |
| recommendation_system | Recommender system |
| nlp_svm | Text classification with SVM |
| time_series | Time series forecasting |
| boosting_algorithms · random_forest · decision_tree | Tree-based models |
| k_means · k_nearest_neighbors · naive_bayes | Clustering and classic classifiers |
| streamlit_ml_app · flask_ml_app | Deploying models as web apps |



