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Natali Kostadinovic

@natalikostadinovic

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Data scientist and statistics student building predictive models and data products.

United States

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What I'm looking for

I am seeking data science or analytics roles where I can build predictive models, engineer features, and create reproducible pipelines while collaborating with interdisciplinary teams and contributing to impactful, data-driven decisions.

I am a statistics student and data scientist experienced in preprocessing complex biomedical signals, engineering features, and building predictive models that improve accuracy and reduce manual effort. I have applied techniques including logistic regression, XGBoost, cross-validation, and SHAP to achieve strong predictive performance.

In research, I built a preprocessing pipeline for 128-channel EEG (filtering, artifact rejection, ICA) that boosted model accuracy to 85% and reduced manual cleaning time by 20%, and engineered ERP and acoustic features to improve perception modeling. I collaborate with faculty and peers in Google Colab to test methods and streamline workflows.

I also bring practical industry QA experience testing app features with TestRail and Postman, designing test cases that cut post-release defects and mentoring offshore QA teams. I enjoy turning data into actionable insights and building dashboards, forecasts, and reproducible pipelines.

Experience

Work history, roles, and key accomplishments

Current

Teaching Assistant

Current

Mount Holyoke College

Sep 2025 - Present (9 months)

Supported 30+ students in Introduction to Statistics by providing R programming help, troubleshooting coding issues, grading assignments, and creating course materials to streamline workflows.

R Statistics Grading Troubleshooting Data Visualization Excel

Data Science Researcher

Mount Holyoke College

May 2025 - Aug 2025 (3 months)

Built preprocessing pipeline for 128-channel EEG data and engineered ERP and acoustic features, raising model accuracy to 85% and reducing manual cleaning time by 20%. Developed logistic regression and XGBoost models with 5-fold CV and SHAP analysis to improve perception modeling.

Python XGBoost Logistic Regression EEG Preprocessing Cross Validation SHAP Google Colab

Software Quality Assurance Engineer

Lodestone

Mar 2021 - Aug 2021 (5 months)

Tested Meta app features using TestRail and Postman, designed and executed test cases that reduced post-release defects by 15%, and mentored offshore QA teams to accelerate cycles by 25%.

TestRail Postman Manual Testing Testing Design Regression Testing Jira

Education

Degrees, certifications, and relevant coursework

Mount Holyoke College

Bachelor of Arts, Statistics

Grade: 4.0/4.0

Pursuing a B.A. in Statistics with coursework in intermediate statistics, linear algebra, data structures, applied machine learning, and data visualization; expected graduation May 2026.