Margarida Antunes Email and Phone Number

Developing comprehensive pricing models for second-hand vehicles, using data analysis, market trends, and historical data, for different EU markets. Direct communication with teams from multiple EU countries to accurately assess business needs, and regional market fluctuations.

As part of the Operations Data Science team, I have worked on different projects to optimize the company's operations and logistics. Recently, I've focused on leveraging NLP techniques to extract valuable insights from large volumes of textual data. From sentiment analysis to text classification and named entity recognition, I harnessed NLP algorithms to drive meaningful outcomes for the business. These models allowed us to understand customer preferences, sentiment, and feedback, improving overall customer experience and driving revenue growth.

Worked in the Intelligent Systems department, mainly focusing on time-series signal processing, and pattern recognition. Developed a Machine Learning model to predict the diagnosis of patients with Amyotrophic Lateral Sclerosis (ALS) using different types of signals. Involved in the maintenance of TSFEL and creation of TSSEARCH, both python libraries related to the extraction of features from time-series.

Student of Master's Thesis in Biomedical Engineering at Fraunhofer AICOS, with the theme "Towards amyotrophic lateral sclerosis interpretable diagnosis using surface electromyography". The goal of the dissertation was to develop a Machine Learning algorithm capable of predicting the diagnosis of patients with Amyotrophic Lateral Sclerosis (ALS), using innovative surface electromyography characteristics.

Optimized datasets’ analysis, in order to predict a person’s motion using Machine Learning approaches. Analysed data from mobile phone’s sensors, using Python.