Data Analyst passionate about transforming data into actionable insights through Business Intelligence, Machine Learning and interactive analytics solutions.
Currently building projects with Power BI, Python, SQL and Streamlit while strengthening my software engineering background through the 42 programming curriculum.
Stack: Python • Scikit-Learn • Streamlit • SQL • Supabase • Docker • GitHub Actions • Docker Hub • Render
An end-to-end Machine Learning platform for transcriptomic cancer classification using RNA-Seq data. OncoLens combines predictive models, interactive dashboards and a clinical decision support application within a production-ready cloud architecture.
Key Features
- Two-stage Machine Learning classification (Tumor vs Normal + Cancer subtype)
- Interactive Streamlit application for clinical decision support
- RNA-Seq data processing, analysis and visualization
- Interactive PCA and analytics dashboard
- Patient management and prediction history with Supabase
- Docker containerization
- Automated CI/CD pipeline with GitHub Actions, Docker Hub and Render
- Cloud deployment following MLOps best practices
🔗 Project Website: https://bootcamp-da-p2.github.io/OncoLens/
🔗 Live Demo: https://oncolens-amc5.onrender.com
🔗 Repository: https://github.com/nsfacila/OncoLens
Alongside Data Analytics, I have developed a solid software engineering foundation through the 42 programming curriculum, working with C, algorithms, data structures and collaborative software development.
More recently, I have expanded my expertise by building complete data products that integrate data analysis, Machine Learning, Business Intelligence, cloud deployment and CI/CD pipelines. This combination has strengthened my analytical thinking, debugging skills and understanding of software architecture, enabling me to transform data into scalable, production-ready solutions.
Business Intelligence: Power BI, DAX, Data Modelling, ETL
Data Analytics: Python, Pandas, NumPy, SQL
Machine Learning: Scikit-Learn, Predictive Modelling, Statistical Analysis, Streamlit
Cloud & MLOps: Docker, GitHub Actions, Docker Hub, Render, Supabase
Development: Git, GitHub, Linux, C
- Portfolio: https://nsfacila.github.io/portfolio/
- LinkedIn: https://www.linkedin.com/in/noelia-sanchez-facila/
- Web Oncolens: https://bootcamp-da-p2.github.io/OncoLens/
- Live Demo: https://oncolens-amc5.onrender.com
- Email: nsfacila@hotmail.com
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I'm currently looking for opportunities as a Data Analyst, Business Intelligence Analyst or Junior Data Scientist, where I can combine analytics, Machine Learning and Business Intelligence to build data-driven solutions that create real business value.