- Blog
- CV generator
- Community
- Documentation
João Paulo de Souza Böger
Florianopolis, Brazil
• Brazilian physicist with 7+ years of experience with science and data, strong mathematics and statistics background, was member of several research groups where I learned how to apply my knowledge and skills to solve real problems. • In 2022 I started working as Data Analyst, further developing my experience dealing with data, from data extraction and database's maintanance, to ML models development and implementation.
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
78
CodersRank Rank
Top 6%
Top 50
Solidity
Developer
Brazil
Highest experience points: 0 points,
0 activities in the last year
Python
31.5
exp.
Jupyter Notebook
29.8
exp.
JavaScript
6.4
exp.
JSON
5.5
exp.
Solidity
4.8
exp.
List your work history, including any contracts or internships
Demarco
Nov 2022 - May 2023 (6 months)
Business Intelligence Specialist
• Develops strategies and Machine Learning models to better understand and predict employee absenteeism, also analyze companywide surveys for a 10,000+ workforce (Python, sk-learn, SQL, seaborn, Matplotlib, Numpy).
• Deploys models to cloud, automate its execution and dashboards updating (Digital Ocean, Python, SQL, Power BI, Matplotlib).
• Data modelling, extraction and maintenance of Databases and Data Lakes (SQL Server, Vertica, Azure).
• Data viz (Power BI, Tableau, Pentaho).
• Reports (Report Builder).
• Deploys models to cloud, automate its execution and dashboards updating (Digital Ocean, Python, SQL, Power BI, Matplotlib).
• Data modelling, extraction and maintenance of Databases and Data Lakes (SQL Server, Vertica, Azure).
• Data viz (Power BI, Tableau, Pentaho).
• Reports (Report Builder).
Connvert
Apr 2022 - Sep 2022 (5 months)
Data Analyst
• I worked extacting and treating data in order to be used to develop score models for the sales department.
• The databases had several-million rows and needed optimal solutions and processes to be dealt with.
• Machine learning models and strategies (Random Forest, XGBoost, LightGBM) targeting the propensity of sales' success.
• Exploratory data analysis, business analytics reports development and maintenance (Excel, Power BI, QlikView).
• Deploying the score models to our internal portal (Docker, Django).
• The databases had several-million rows and needed optimal solutions and processes to be dealt with.
• Machine learning models and strategies (Random Forest, XGBoost, LightGBM) targeting the propensity of sales' success.
• Exploratory data analysis, business analytics reports development and maintenance (Excel, Power BI, QlikView).
• Deploying the score models to our internal portal (Docker, Django).
UNESP - Universidade Estadual Paulista
Feb 2020 - Feb 2022 (2 years)
FAPESP Master's Researcher
• As a LHC member I searched how to identify dark matter signatures at the Tracker System of the CMS detector.
• From the charged particle hits at the Tracker System, I implemented a Combinatorial Kalman Filter (CKF) algorithm that searches and reconstructs which hits belong to which particle and fits its trajectory through chi^2.
• The theoretical formulation of the problem was conceived in cylindrical coordinates, also the fitting, and the dynamical equations of a charged particle embedded in a transverse magnetic field were solved using 4th and 5th order Runge-Kutta through SciPy, NumPy and Matplotlib for visualization.
Particle collisions' generation, events with dark matter production (FIMP model) with charginos (SUSY theory) as intermediate, through Monte Carlo simulations in the CMSSW framework C++
• Exploratory data analysis of data from the simulation to find and characterize the results, by comparison with the state-of-the-art analysis of the area, using Pandas, SciPy, scikit-learn and Matplotlib
Studying the frequency distribution of the particles and tracks' parameters, their correlation and resolution of its reconstruction we were able to conclude that dark matter signals could be detected with the increasing energy of the LHC collider, being a possible pioneer discovery of dark matter particles.
• From the charged particle hits at the Tracker System, I implemented a Combinatorial Kalman Filter (CKF) algorithm that searches and reconstructs which hits belong to which particle and fits its trajectory through chi^2.
• The theoretical formulation of the problem was conceived in cylindrical coordinates, also the fitting, and the dynamical equations of a charged particle embedded in a transverse magnetic field were solved using 4th and 5th order Runge-Kutta through SciPy, NumPy and Matplotlib for visualization.
Particle collisions' generation, events with dark matter production (FIMP model) with charginos (SUSY theory) as intermediate, through Monte Carlo simulations in the CMSSW framework C++
• Exploratory data analysis of data from the simulation to find and characterize the results, by comparison with the state-of-the-art analysis of the area, using Pandas, SciPy, scikit-learn and Matplotlib
Studying the frequency distribution of the particles and tracks' parameters, their correlation and resolution of its reconstruction we were able to conclude that dark matter signals could be detected with the increasing energy of the LHC collider, being a possible pioneer discovery of dark matter particles.
This section lets you add any degrees or diplomas you have earned.
Universidade Estadual Paulista Júlio de Mesquita Filho
Mestrado, Física
Feb 2020 - Feb 2022
Universidade Federal de Santa Catarina
Bacharelado, Física
Feb 2016 - Feb 2020