M.Sc. student in Statistics & Data Science (Tel Aviv University, 2025–2027) · Data Scientist at DataMED Lab, Tel Aviv University · B.Sc. Statistics & Data Science & B.A. Business Administration (Hebrew University of Jerusalem, 2022–2025, GPA 90)
Python · PyTorch · TensorFlow · scikit-learn · SQL · R · MATLAB · pandas · NumPy · transformers · spaCy · GLMs & regression · deep learning · time series · Tableau · Power BI · Git · statistical modeling · ML/LLM pipelines · evaluation & error analysis
Programming: Python (NumPy, pandas, scikit-learn, TensorFlow, PyTorch), R, SQL, MATLAB
Machine learning & algorithms: Regression, GLM, random forests, SVM, neural networks, deep learning, reinforcement learning, time series, simulation, data structures & algorithms, hypothesis testing, optimization
Applied data science: Data preprocessing, feature engineering, statistical modeling, model training, evaluation, error analysis
Visualization & BI: Tableau, Power BI, matplotlib, ggplot2
Tools: Git, advanced Excel
NLP / LLM stack (where relevant): transformers, spaCy
I train and evaluate machine learning and deep learning models in Python on large-scale data, with a strong base in algorithms, statistical modeling, and end-to-end ML pipelines. At DataMED Lab I work on clinical and imaging data (including MRI and physician reports): ML/LLM solutions for information extraction, prediction, and automated workflows; tools for evaluation, error analysis, and performance optimization; and collaboration with clinical and research teams on scalable methods.
Earlier experience: Student Data Analyst at the Israel Ministry of Finance (SQL, Excel, R, BI); Implementation Specialist at Ness Technologies (SAP financial data).
Languages: Hebrew (native) · English (fluent)
- cyber-asset-risk-analytics — Asset–vulnerability risk scoring (CVSS), legacy vs. improved metrics, remediation simulation, LLM-assisted device metadata enrichment
- trial-conversion-prediction-ml — B2B trial-to-paid prediction: time-based split, XGBoost vs. baselines, calibration, SHAP, monthly MAE/MAPE
- Loan-Approval-Prediction-System-Machine-Learning-Project — Credit default modeling and transparent recommendations
- University-Projects — Academic work in Statistics & Data Science (HUJI)
Static HTML reports (read-only exports): Cyber asset risk · Trial conversion — if a link returns 404, wait 1–2 minutes after push or check Settings → Pages (source: main / /docs).