Data Scientist | Machine Learning & Explainable AI (XAI)
São Paulo, Brazil · Portuguese Citizenship (European Union)
📱 +55 11 93940-2610
✉️ [email protected]
🔗 https://www.linkedin.com/in/helio-henrique-dias-54a982239/
PROFESSIONAL SUMMARY
Data Scientist with strong academic and applied background in Machine Learning, Data Mining, and Explainable Artificial Intelligence (XAI). PhD researcher in Computer Science with experience in predictive modeling, data stream analysis, ETL pipelines, and business intelligence. Proven ability to translate complex data into actionable insights and transparent decision-support systems.
PROFESSIONAL EXPERIENCE
Data Scientist
Lello Lab (lellolab.com.br)
July 2022 – Present
- Design, development, and deployment of data-driven solutions for business intelligence and analytics.
- Construction of analytical dashboards using Power BI to support strategic and operational decision-making.
- Implementation of ETL pipelines (Extract, Transform, Load) for structured and unstructured data sources.
- Application of statistical analysis and machine learning techniques to identify patterns, trends, and performance drivers.
- Collaboration with business stakeholders to translate analytical results into actionable insights.
Data Scientist (Research Project)
University of São Paulo (USP)
January 2021 – January 2022
- Industry-sponsored applied research project in machine learning.
- Development of predictive models for human movement pattern recognition using smartphone motion sensor data.
- Data preprocessing, feature engineering, model training, validation, and performance evaluation.
- Analysis of model robustness and generalization under real-world data variability.
Software & Data Engineering Intern
Mauá Institute of Technology
Second Semester, 2018
- Development of relational database systems for partner companies.
- Migration of Excel-based operational records into structured database environments.
- Design and implementation of a Java-based application with graphical interface for database management and querying.
EDUCATION
PhD in Computer Science (Ongoing)
UNIFESP – Instituto de Ciência e Tecnologia (ICT)
June 2024 – Present
Research Areas:
Machine Learning, Data Mining, Explainable Artificial Intelligence (XAI), Data Streams
Thesis:
Interpretability of Dynamic Models in the Context of Big Data
Selected Coursework:
- Analysis of Algorithms and Data Structures
- Neural Networks
- Artificial Intelligence
- Computational Intelligence in Chemistry
- Scientific Methodology
- Directed Studies I & II
- Research Seminars
MBA in Data Science
University of São Paulo (USP) – ICMC São Carlos
2021 – 2022
Focus on Machine Learning, Massive Parallel Data Processing, Statistics for Data Science, Neural Networks and Deep Learning Architectures, and Advanced Data Capture and Processing Techniques.
Bachelor’s Degree in Computer Engineering
Mauá Institute of Technology
2014 – 2019
PUBLICATIONS
Dias, H. H. (2026).
Explainable Artificial Intelligence for Data Stream Mining: Interpretability Challenges in Dynamic Learning Environments.
Manuscript under review.
This work investigates interpretability challenges in machine learning models operating on non-stationary data streams, analyzing the effects of concept drift on explanation stability and proposing methodological frameworks for explainable real-time predictive systems.
CERTIFICATIONS
Professional Data Scientist – DataCamp
https://www.datacamp.com/certificate/DS0029356383637
TECHNICAL SKILLS
- Programming: Python, Java
- Data Science & ML: Machine Learning, Statistical Modeling, Feature Engineering, Model Evaluation
- Explainability: Model-agnostic XAI methods, interpretability under concept drift
- Data Engineering: ETL pipelines, data preprocessing
- BI & Visualization: Power BI
- Databases: Relational databases, structured data modeling
LANGUAGES
- Portuguese – Native
- English – Advanced (C1 – CEFR)