Research / Product Analyst focused on neuroscience and digital health.

I build reproducible data projects at the intersection of:

• SQL and product analytics
• EEG / fMRI / sleep data
• machine learning evaluation
• leakage-aware validation
• interpretable research workflows
• digital health MVPs

• SQL / product analytics
• I can turn an open-ended research question into a reproducible data analysis pipeline.
• I focus on validation quality, leakage risks, class imbalance and honest limitations.
• I combine research-style analysis with product thinking: metrics, dashboards, user behavior and decision-making.
• I am especially interested in sleep, cognitive load, neurotechnology, mental health analytics and digital health products.

PostgreSQL product analytics case for a synthetic sleep-tracking app.

Focus: SQL, cohort retention, onboarding funnel, A/B testing, churn-risk segmentation, business recommendations.

This project demonstrates how I translate product event data into decisions: activation opportunities, acquisition channel quality, retention analysis and lifecycle interventions.

EEG cognitive load classification project using spectral bandpower features, classical ML baselines, CNN modeling and Streamlit demo.

Focus: EEG, ML validation, leakage analysis, subject-independent validation, feature importance.

The key part of this project is the comparison between optimistic window-level validation and more realistic subject-independent validation.

Sleep-tech product analytics and ML MVP with synthetic user-day data, sleep-quality prediction, threshold analysis, Streamlit dashboard and rule-based AI sleep coach.

Focus: product metrics, ML evaluation, threshold tuning, dashboarding, safe non-medical AI logic.

This project shows how ML outputs can be connected to product decisions and user-facing recommendations.

Exploratory resting-state fMRI functional connectivity analysis across psychiatric diagnostic groups.

Focus: fMRI, connectivity matrices, permutation testing, FDR correction, research interpretation.

This project demonstrates a reproducible neuroscience workflow with careful limitations and no overclaiming.

Sleep-EDF based sleep-staging and fragmentation-analysis project.

Focus: hypnogram processing, sleep-stage classification, confusion matrix analysis, fragmentation metrics.

This project connects baseline sleep-stage predictions with downstream sleep-quality metrics.

• SQL / PostgreSQL
• Python
• pandas / NumPy
• product analytics
• cohort analysis / retention / funnels
• A/B testing
• scikit-learn
• machine learning evaluation
• EEG / fMRI / sleep data analysis
• Streamlit dashboards

I am building a focused portfolio for roles in:

• data analytics;
• research analytics;
• product analytics;
• healthtech / digital health analytics;
• neuroscience and sleep-tech analytics.

My goal is to work on data problems where behavioral, physiological or product data can be translated into clear insights, validated models and useful user-facing decisions.