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Data & Applied Scientist II
Advanced knowledge and experience in the development of data science solutions involving: - Problem definition, model validation and prototypes development through strong interactions with domain experts; - Machine learning algorithms (R and Python) applying ML classic models and deep learning models (images, sounds and free texts) for classification and regression tasks; - MLOps pipelines with train and predict flows through continuous data stream; - Interactive dashboards (PowerBI, Shiny/R and Streamlit/Python); - Infrastructure for storage and processing of massive data (Spark, Impala and Hadoop). • Software skills: o Microsoft Office, Microsoft PowerBI, Microsoft Visual Basic, MatLab, RapidMiner and Weka • Programming skills: o Advanced knowledge in SQL, R, Python, Ruby, Java and C++ • Data science (modeling) skills: o Scikit Learn, xgBoost, LightGBM, TensorFlow and PyTorch (Python modules) o TensorFlow in time series analysis (forecast and classification) and PyTorch in natural language processing and image analysis • Data visualization skills: o Prototype with StreamLit (Python module) and Shiny (R module) • MLOps skills: o Pipeline orchestration with Luigi and AirFlow (Python modules) o Deploy with Docker and Kubernetes • Data engineering skills: o Advanced knowledge in SQLite, MySQL, Microsoft SQL Server, PostgreSQL and Oracle DB o Basic knowledge in Hadoop ecosystem (Impala, Hive) and MongoDB NOTE: SQL, R, Python are programming languages applied daily in the development of machine learning solutions/pipelines.
Georgia Institute of Technology
Master's degree, Big Data Analytics
January 1, 2020 – January 1, 2025
INPE - Instituto Nacional de Pesquisas Espaciais
Master's degree, Data Science
January 1, 2015 – January 1, 2018
Washington University
Associate's degree, Machine Learning
January 1, 2014 – January 1, 2014
FAAP - Fundação Armando Alvares Penteado
Master in Business and Administration, Marketing Management
January 1, 2007 – January 1, 2010
Universidade Federal de Itajubá
Engineer, Electrical Engineer
January 1, 2002 – January 1, 2006
Microsoft
Data & Applied Scientist II
April 1, 2021 – Present
São Paulo, São Paulo, Brazil
Hospital Albert Einstein
Senior Data Scientist
May 1, 2019 – April 1, 2021
São Paulo, São Paulo, Brazil
TOTVS Labs
Senior Data Scientist
October 1, 2016 – May 1, 2019
São Paulo Area, Brazil
Embraer
Data Scientist
January 1, 2014 – September 1, 2016
São José dos Campos Area, Brazil
Embraer
Knowledge Engineer
January 1, 2010 – December 1, 2013
São José dos Campos Area, Brazil
Embraer
Product Development Engineer
May 1, 2007 – December 1, 2009
São José dos Campos Area, Brazil
CPFL Energia
Intern
January 1, 2006 – December 1, 2006
Campinas Area, Brazil
AREVA T&D
Intern
May 1, 2005 – December 1, 2005
Itajubá Area, Brazil
Furnas-Centrais Eletricas
Intern
April 1, 2005 – May 1, 2005
Lorena Area, Brazil
Machine Learning Foundations: A Case Study Approach
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning multiple industries (aviation, healthcare, education, energy) and roles from engineering to data science. This breadth of experience suggests adaptability and a willingness to tackle varied challenges, which could contribute positively to cultural fit in a dynamic environment. The progression from Electrical Engineer to Data & Applied Scientist demonstrates a strong drive for continuous learning and career evolution. However, the target role of 'Data Analyst' might be a step down from their 'Data & Applied Scientist II' and 'Senior Data Scientist' roles, potentially indicating a mismatch in career trajectory or expectations, or a strategic pivot. The lack of specific project details for the most recent role at Microsoft makes it difficult to fully assess current alignment.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight collaboration with doctors/nurses and business areas, suggesting strong communication and stakeholder management skills. Their involvement in defining project scope and acting as a technical advisor indicates leadership and problem-solving abilities. The diverse project portfolio suggests adaptability and a proactive approach to learning new domains.