Pedro H.Data Scientist
Skills
Data Scientist specializing in the development of data-driven products aimed at enhancing revenue and reducing costs through Data Analysis, Business Intelligence, and Machine Learning techniques. Expertise includes product classification, Key Value Item selection through customer behavior analysis, and the application of Graph Theory in analytical processes. Proficient in managing product recommendation models, calculating performance metrics, and automating processes using SQL, Python, PySpark, and visualization tools such as Power BI.
Previous experience includes developing Lifetime Value (LTV) calculation models and business metrics projection models for customer acquisition and retention. Created dashboards using Shiny R for metric consultations and analyzed advertisement outcomes using R language and RStudio.
Educational background includes an MBA in Data Science & Analytics, with a focus on Machine Learning techniques such as Clustering, Correspondence Analysis, Factorial Analysis (PCA), GLM/GLMM Regressions, Time Series Analysis, and Tree Models, along with a strong foundation in Statistics and Hypothesis Testing. Currently pursuing further education in Technology for Business: AI, Data Science & Big Data while actively engaging in ongoing studies within the Data Science community.
Research experience includes two years in Field Theory during undergraduate studies, culminating in three published scientific papers internationally. Master's degree research focused on Particle Physics, resulting in participation in an international publication. The overarching goal is to excel as an independent Data Scientist, devising solutions that significantly enhance business outcomes.
Data Scientist
8/1/2022 - Present
Developed expertise in machine learning and data science, focusing on the analysis and construction of machine learning models. Proficient in Python and R for statistical analysis and model development. Utilized frameworks such as TensorFlow, Keras, and Scikit-learn for building and deploying models. Demonstrated skills in data preprocessing, feature engineering, and model evaluation. Conducted exploratory data analysis (EDA) using Pandas, NumPy, and Matplotlib. Leveraged cloud platforms like AWS and Google Cloud for scalable computing resources. Employed version control systems such as Git for collaborative code maintenance and model versioning. Ensured models were production-ready, adhering to reproducibility and performance standards. Published detailed documentation and presented findings to stakeholders, highlighting the impact of machine learning solutions on business outcomes.Data Analyst/Data Scientist
9/1/2021 - 6/1/2022
Gained substantial expertise in data analysis and data science, focusing on deploying both supervised and unsupervised machine learning models. Worked extensively with deep learning and time series analysis to derive insights and inform strategic decisions. Excelled in data visualization and dashboard construction to present business metrics and projections effectively. Provided technical support to the team, fostering a collaborative environment. Developed proficiency in R, Python, and SQL, leveraging these tools for robust data manipulation and analysis.
Physics at São Paulo State University Júlio de Mesquita Filho
2011 - 2015Elementary Particle and Field Physics at São Paulo State University Júlio de Mesquita Filho
2016 - 2017Technology for Business: AI, Data Science and Big Data at Pontifical Catholic University of Rio Grande do Sul
2024 - 2025Data Science and Analytics at MBA USP/Esalq
2021 - 2022
Certification Training AZ-900: Microsoft Azure Fundamentals at Alura
8/1/2021SQL Training with Microsoft SQL Server 2017 at Alura
8/1/2021Statistics with R: Correlation and Regression at Alura
7/1/2021Statistics with R: Hypothesis Testing at Alura
7/1/2021Data Science Training at Alura
7/1/2021Machine Learning Training at Alura
7/1/2021Data Analysis: Introduction with R at Alura
6/1/2021Data Analysis and Visualization: Data Science with R at Alura
6/1/2021Statistics with R: Probability and Sampling at Alura
6/1/2021Machine Learning: Clustering with R at Alura
6/1/2021STATISTICS II: DEEPENING IN HYPOTHESES AND CORRELATIONS at Alura
5/1/2021Statistics I: Understand Your Data with R at Alura
5/1/2021Statistics with R: Frequencies and Measures at Alura
5/1/2021Statistics with R: Introduction to Modeling at Alura
5/1/2021Statistical Training with Python at Alura
5/1/2021Python Training for Data Science at Alura
5/1/2021Python for Engineers and Scientists/ Basic to Advanced at Udemy
5/1/2021Python Training at Alura
4/1/2021Python Programming from Basic to Advanced at Geek University
4/1/2021
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