Roberto de la Cámara
Data ScientistMadridMember since June 21, 2026
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ML-IDS
March 1, 2026 – Present
Full-stack ML intrusion detection system. Random Forest + Stacking Classifier on CIC-IDS2017 (78 features). FastAPI, async PostgreSQL, real-time WebSocket dashboard, Prometheus metrics, MLflow tracking, API key auth.
View ProjectResearch-Agent
January 10, 2026 – Present
Autonomous research agent — 10 sources in parallel, self-correcting loop, exports PDF/Word/HTML. Powered by LangGraph + Ollama.
View ProjectCognitiveNetworkAnomalyDetector
December 27, 2025 – Present
Network anomaly detection with triple-engine ensemble: Isolation Forest (40%) + LSTM Autoencoder/PyTorch (40%) + rule-based (20%). Scapy packet capture, 18 per-IP features, MLflow tracking, Streamlit dashboard.
View ProjectHopfieldAssigmentProblemSolver
September 20, 2025 – Present
Hybrid microservices architecture (Go/Gin API Gateway + Python/Flask Hopfield Solver) for assignment problems using Hopfield neural networks. Docker Compose, Nginx reverse proxy, Jenkins CI/CD.
View ProjectCognitive-Intrusion-Detection-System
March 28, 2025 – Present
Cognitive Network Defense System (CNDS). 4 detection engines (RF, Isolation Forest, LSTM Autoencoder, rules), Scapy capture, ensemble scoring, FastAPI with JWT/RBAC, GeoIP enrichment, alert correlation, adaptive weights.
View ProjectHopfieldSPP
November 24, 2024 – Present
Shortest path problem solver using Hopfield neural networks with TensorFlow 2.x. Three model versions: Original, Improved (95-100% optimal), Advanced (sparse tensors, attention, 5000+ nodes). FastAPI REST API.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and highly technical, focusing on advanced machine learning and system development. This indicates a strong passion for technology and self-driven learning. The diversity of projects, from network security to optimization problems and autonomous agents, suggests adaptability and a broad interest in applying data science. However, without team-based project experience or work history, assessing collaboration and broader cultural fit is limited.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong technical drive and ability to complete complex projects independently.