Nicolás Tamajón Rivas

Data Scientist and ML Engineer specialized in predictive modeling, data analysis, and Python-based automation. I help companies turn raw data into actionable insights by building end-to-end machine learning solutions, analytical dashboards, and efficient backend tools.

With a strong background in mathematics, civil engineering, and a Master’s in Deep Learning, I combine technical depth with practical problem-solving. I have hands-on experience working with real-world datasets (industrial sensors, SCADA, SQL Server, business operations), building models for classification, regression, time series forecasting, and anomaly detection.

What sets me apart

- Full-stack Data Science approach: data cleaning, feature engineering, modeling, validation, deployment simulation

- Experience with industrial and operational data workflows (PLC → SCADA → Historian → SQL Server → Power BI)

- Strong communication skills to explain technical results in clear business terms

- Python development experience (Flask, Django, FastAPI) plus knowledge of Docker, Kubernetes, AWS, MLflow, ZenML

Types of projects I typically handle

• Machine learning models (classification, regression, forecasting, anomaly detection)

• Exploratory data analysis and insights reporting

• Power BI dashboards and data visualizations

• Backend development and process automation in Python

• ML pipelines and MLOps setup (MLflow, Docker, ZenML)

• Data consulting: structuring data projects or improving reporting workflows

Typical deliverables

• Fully trained ML models + notebooks + documentation

• Interactive dashboards (Power BI or Python)

• APIs and automation scripts

• Executive reports with insights and recommendations

• Reproducible ML/ETL pipelines (Docker, MLflow, ZenML)

If you need someone who can understand your data, build a reliable solution, and deliver clear results, I’d be happy to help.