Ricardo Urdaneta
Data Analyst
Data Analyst focused on transforming datasets into actionable operational insights. Skilled in Python, SQL, Excel and Power BI/Tableau for data wrangling, automated reporting, and interactive dashboard development.

Publicaciones
Building a RAG Assistant to explore my technical Portfolio
Fine-tuning an open-source 7b parameter LLM on local hardware
Data Synthesizer: How I built a tabular data generator
Projects
Data analysis project covering everything from the automated extraction of historical meteorological records via API for Chile's 16 regional capitals to the development of an interactive dashboard. The objective is to monitor the evolution of temperatures and rainfall over the last decade, identifying climate patterns and regional anomalies through the integration of Python for data processing and dynamic visualization.
Python
Geospatial analysis project focused on the visualization of pollutant emissions from diffuse sources (agricultural burning and residential wood combustion) across Chile. It utilizes Python-based data processing and interactive cartography to map emission density at the communal level, enabling the identification of environmental hotspots and supporting air quality monitoring between 2019 and 2023.
Python
Data analysis project covering everything from data cleaning and modeling of over 22,000 records using Power Query to the creation of a Power BI dashboard. The objective is to identify critical workplace burnout and mental fatigue factors, validating hypotheses on the impact of overtime and work-life balance to propose data-driven talent retention strategies.
Power BI
Data analysis project covering the cleaning of 1.8M records from ODEPA, memory optimization with PARQUET, to interactive app deployment. The goal is to visualize the evolution and regional gaps in food prices in Chile (2020-2025).
Python
Natural Language Processing (NLP) project covering everything from text data cleaning and tokenization to the implementation of sentiment analysis models on thousands of movie critic reviews. The objective is to automatically classify opinions as positive or negative and extract semantic patterns using Python and text mining techniques to understand the critical perception of various cinematic productions.
Python




