Natalia Pereira

Delivered end-to-end data solutions in the telecom sector, combining ML engineering, data pipeline development, and business intelligence to support strategic decision-making at scale. Machine Learning & AI: - Improved anomaly detection F1-score from 5% to 89% through feature engineering on 81M+ records and ensemble modeling (Isolation Forest + Random Forest) - Built and deployed ML models as REST APIs using Flask, integrating them into production ETL pipelines with runtime monitoring and alerting - Applie

Conducted data science research in biomedical engineering, combining signal processing, computer vision and statistical modeling applied to healthcare data. - Researched the impact of MRI artifacts on cancer detection models using TensorFlow and ResNet-50, contributing to a scientific publication - Developed time-series models of biosignals (ECG, blood pressure, respiration) in elderly stroke patients using MATLAB, FFT, ARX and ANOVA - Completed a 1-year academic exchange at the University of Porto, focusi

Contributed to anomaly detection and Explainable AI research projects, developing ML solutions applied to customer data and computer vision. - Analyzed and classified anomalies in customer registration data, developing feature extraction strategies using Python, NLP and ML models (Random Forest, Isolation Forest) - Developed Proofs of Concept for Explainable AI (XAI) applied to computer vision and tabular data using SHAP, LIME, ELI5 and Integrated Gradients - Supported data pipeline development and explora

- Developed a scheduling page and viewing medical appointments, using JavaScript React and following the FHIR (Fast Healthcare Interoperability Resources) standard. - Integrated the scheduler page with the database requests.

Supported quantitative regulatory studies in Brazil's energy sector, delivering data-driven insights for evidence-based policy decisions. - Analyzed productivity gains and operational efficiency of electricity distribution companies (Public Consultation No. 7/2019) - Contributed to WACC estimation for electricity generation, transmission and distribution sectors (Public Hearing No. 9/2019) - Investigated technical and non-technical loss data to identify performance gaps and support policy recommendations (

Held progressive leadership roles in a junior consulting enterprise, growing from Marketing Advisor to Chief Operating Officer. - Restructured administrative, financial and strategic operations, increasing revenue by 60% and number of projects by 50% - Developed strategic planning for 2018, responsible for doubling revenue and projects the following year - Led People Management and aligned directors with company strategic goals Skills: Leadership · Strategic Planning · Data Analysis · Operations Managemen

MBA in Artificial Intelligence and Big Data from ICMC USP - Thesis: Prediction of Protein Function with Machine Learning - An Analysis of the CAFA 5 Competition - Relevant coursework: Deep Learning, LLMs, Protein Structure Analysis - GPA: 9.7/10

Exchange at the Faculty of Engineering of the University of Porto, studying subjects of the Integrated Master in Bioengineering and the Integrated Master in Electrical and Computer Engineering: Neuroengineering, Biomedical Instrumentation, Modeling in Biomedical Engineering, Market Economics and Fo

- Thesis: Quantification of Autonomic Nervous System Activity in Elderly Subjects with Stroke - Relevant coursework: AI, Computer Vision, Signal Processing - GPA: 4.51/5