Rafael N.

Data Scientist

Data Scientist
10/1/2023 - Present

Analyzed and developed predictive models for assessing risk related to the tax on gratuitous transfers of goods for the state tax administration of Rio Grande do Sul. The role required advanced proficiency in statistical analysis, machine learning, and data modeling. Utilized tools and frameworks such as Python, R, and SQL for data analysis and model development. Employed machine learning libraries like scikit-learn and TensorFlow to enhance predictive accuracy. Ensured data integrity and collaboration by using version control systems such as Git. Implemented models that significantly improved the efficiency and accuracy of risk assessments, contributing to more effective tax administration.

Data Scientist
12/1/2021 - 8/1/2023

Developed extensive expertise in leveraging API frameworks and the Plumber library for building and managing RESTful web services. Gained proficiency in containerization and orchestration tools, notably Docker, to streamline development and deployment processes. Utilized GitHub for version control and collaborative code maintenance, ensuring robust and scalable development workflows. Demonstrated skills in using Azure AutoML to automate machine learning model training and deployment. Mastered programming languages including R, Python, and SQL, to perform complex data analysis, orchestrate machine learning pipelines, and manage database operations effectively.

professor
5/1/2021 - 8/1/2021

Assumed responsibility for the discipline of Biostatistics for graduate students, developing extensive expertise in statistical analysis methods and data interpretation. Utilized advanced statistical software tools including R, SAS, and SPSS for instructional purposes and data analysis. Implemented interactive teaching methods to facilitate understanding of complex biostatistical concepts. Guided students in using platforms such as Python for statistical computing and data visualization. Designed and executed curriculum involving regression analysis, survival analysis, and multivariate analysis. Emphasized practical applications and research proficiency, fostering analytical skills essential for research in health sciences. Led workshops and seminars to enhance methodological rigor and advanced statistical techniques among graduate students. Demonstrated strong abilities in academic mentorship and guidance, contributing significantly to the students' scholarly and professional development in the field of biostatistics.

professor
8/1/2018 - 12/1/2021

Held the role of teaching trainee and academic advisor in the Statistics discipline for undergraduate courses. Served as the professor responsible for the Data Processing class, providing instruction on essential data management and analysis techniques. Conducted specialized courses on the R programming language, emphasizing its application in animal breeding. Developed a comprehensive understanding of statistical methodologies and data processing tools. Demonstrated proficiency in curriculum development and student advisement, fostering a collaborative learning environment. Applied technical expertise in R to streamline data analysis processes and enhance educational outcomes in animal genetics.

PhD research student
7/1/2018 - 4/1/2022

Executed a comprehensive doctoral dissertation focused on gene expression in beef cattle and the prediction of animal behavior utilizing Machine Learning techniques paired with accelerometer data. Achieved deep expertise in genomic sequencing, bioinformatics, and statistical analysis tools including R and Python for data manipulation and visualization. Implemented various Machine Learning algorithms such as Random Forest, Support Vector Machines, and Neural Networks for predictive modeling, leveraging TensorFlow and scikit-learn frameworks. Analyzed large datasets using SQL for database management and integration. Ensured the accuracy and effectiveness of predictive models through cross-validation, confusion matrices, and other metrics. Developed proficiency in handling accelerometer data, managing preprocessing stages including noise reduction and feature extraction. Collaborated with interdisciplinary teams to integrate biological insights with computational models, enhancing the understanding of the correlation between gene expression patterns and observable animal behaviors. Maintained rigorous data documentation and code version control using Git, ensuring reproducibility and collaborative development.

Animal Science at São Paulo State University Júlio de Mesquita Filho
2011 - 2015

Animal Breeding and Genetics at São Paulo State University Júlio de Mesquita Filho
2018 - 2022

Animal Breeding and Genetics at São Paulo State University Júlio de Mesquita Filho
2016 - 2018

Software Engineering for Data Science at PUC - Rio
7/1/2022