• Experience with several supervised machine learning (Linear Regression, Logistic Regression, Naïve Bayes) and unsupervised machine learning (Decision Trees, Random Forest, XGBoost, K-means, DBSCAN, HDBSCAN, UMAP, PCA, Latent Dirichlet Allocation) methods.
• Experience with most relevant Python libraries such as pandas, NumPy, scikit-learn, TensorFlow, PyTorch, Matplotlib.
• Experience with statistical modeling such as Decision Trees, Time Series Forecasting, Cluster Analysis, Regression Analysis, Bayesian Analysis, Monte Carlo methods.
• Experience extracting and transforming data, and with feature engineering.
• Made decisions on metrics to track and data sources to use for our company’s main games.
• Designed and implemented natural language processing models to perform topic modelling and sentiment analysis on textual data (reviews, questionnaires, Discord channels).
• Designed and implemented unsupervised machine learning models to predict player churn based on metrics of playing behaviour.
• Designed and implemented unsupervised machine learning models to classify players into distinct groups (player personas) based on player behavior data and textual data.
• Performed network analysis on game titles owned by a subset of players of a game
• Made several dashboards and reports with KPI’s and in-game metrics geared towards different company stakeholders.
• Made a Slack bot to alert of new Steam forum posts and their sentiment score.
• Created custom data gathering scripts to extract relevant data from the Steam platform: reviews, users owned and wishlisted games.
• Collaborated with game developers on deciding what data to track in different games.
• Collaborated in designing company’s own database and data flow for gathering and storing game data.
• Collaborate on an ongoing basis with marketing team to implement results of data analyses.

• Proficiency in calculus, linear algebra, game theory, and programming in several languages.
• Developed and analyzed both discrete time and continuous time mathematical models using Wolfram Mathematica.
• Developed and performed agent-based models in MATLAB.
• Developed algorithms for performing computer simulations and analyzing data.
• Performed statistical modelling (time series analysis, regression analysis) on data from computer simulations.
• Wrote four research manuscripts.
• Wrote several research proposals which were awarded with funding.
• Presented research findings in multiple conferences around Europe.
• Taught Philosophy of Science course to incoming doctoral students of the TekNat department.
• TA in the R lab part of the course Evolutionary Patterns for Masters students in the Evolutionary Biology program.

• Performed bioinformatic analyses.
• Statistically analyzed genomic data using bash, Python and R.
• Performed statistical modelling (Approximate Bayesian Computation, clustering).
• Presented research findings via oral communications in multiple conferences in Brazil.
• Wrote one research paper.
• Taught lectures in the Population Genetics course for Biology undergraduates

• Created and maintained websites geared towards affiliate marketing
• Created and maintained databases
• Wrote and optimized blog content
• Designed websites’ interfaces
• Optimized websites’ performance, layout, functionalities, and navigation
• Performed SEO

Education & SKills

MSc Artificial Intelligence

Stockholm University

Upcoming (August 2023)

IBM data science professional

Coursera

PHD Mathematical evolutionary biology

Uppsala University, Sweden

2022

MSC population genetics

Universidade Federal de Minas Gerais, Brazil

2015

BA philosophy

Universidade Federal de Minas Gerais, Brazil

2012

Recent projects