Open to opportunities

Fatjona Murrani

@fatjonamurrani

Message

I build interpretable machine learning models that turn complex data into actionable insights.

Albania

Message

What I'm looking for

I'm seeking opportunities to contribute to cutting-edge data science and AI work, solve real-world problems with data, and continue growing professionally.

I've applied statistical analysis and machine learning to gut microbiome abundance data to model cardiovascular disease risk, using R and SHAP to identify influential microbial features.

As a junior Data Scientist and ML Developer, I preprocessed and explored public transport satisfaction data, then built Linear, Ridge, Random Forest, and Gradient Boosting models to identify key predictors supporting service optimization.

I've also supported hands-on R training for biological data analysis, helping participants apply statistical analysis and reproducible workflows.

With a Bachelor's degree in Mathematics and ongoing Master's studies in Data Science and Artificial Intelligence at the University of Tirana, I'm eager to apply data and AI to real-world challenges.

Experience

Work history, roles, and key accomplishments

Assistant Trainer - BioData Analysis Training School

BioData Analysis Training School

Dec 2025 - Dec 2025 (0 months)

Supported hands-on R training for biological data analysis, assisting participants with statistical analysis and reproducible workflows during the training.

R Statistical Analysis

Research Intern - Data Science & Machine Learning

Microbiome Analytics

Oct 2025 - Oct 2025 (0 months)

Applied statistical analysis and machine learning to gut microbiome abundance data to model cardiovascular disease risk. Preprocessed high-dimensional dataset, performed feature selection and dimensionality reduction, and built predictive models including Random Forest, SVM (CLR + RBF), Elastic Net, and XGBoost.

Statistical Analysis Machine Learning data preprocessing Dimension Reduction Random Forest SVM Elastic XGBoost SHAP R

Data Scientist & ML Developer (Junior Level)

Junior Level

Jan 2025 - Sep 2025 (8 months)

Performed data preprocessing, exploratory analysis, and applied Linear, Ridge, Random Forest, and Gradient Boosting models on public transport satisfaction data to identify key predictors and support service optimization.

data preprocessing Random Forest Gradient Boosting