About Me

Hello, I’m Pablo Freitas, a data analyst passionate about solving real-world problems using data-driven insights. I work with Python to apply mathematical and statistical methods to measurement data — identifying errors, validating signals, and building analysis pipelines that support data quality in engineering contexts.

I’ve also worked on research projects involving hate speech detection from audio, using tools such as OpenSmile, Whisper, and machine learning models for feature extraction and classification.

My Key Strengths:

Signal Analysis & Error Detection: Applying mathematical and statistical approaches to identify anomalies and errors in measurement signals using Python, NumPy, and SciPy.
Data Wrangling: Extensive experience working with large datasets, feature engineering, and cleaning data using Pandas and NumPy.
Data Visualization: Strong skills in communicating findings through visualizations using Matplotlib, Plotly, and Dash.
Speech & Audio Processing: Experience with Whisper for transcription and OpenSmile for audio feature extraction.

You can view some of my projects in the Projects section, where I demonstrate my work in hate speech detection, speech-to-text transcription, and other data-driven solutions.

Feel free to connect with me via LinkedIn or explore my GitHub for more examples of my work!