Hasan Javed

Owned machine learning evaluation for financial intelligence workflows, applying Python, SQL, Rust, C++, scikit-learn to high-impact analytical use cases. Developed predictive models with XGBoost and LightGBM, improving risk-classification precision 18% across benchmark datasets. Built validation frameworks in Python and MLflow, reducing model review cycles 32% through reproducible evaluation pipelines. Designed time-series forecasting models using Prophet, statsmodels, and tigramite.

Developed fraud propensity models using Python, SQL, XGBoost, improving recall 19% while maintaining precision targets. Built feature engineering pipelines with Spark and Airflow, reducing training dataset generation time 44%. Designed controlled experiments using statsmodels and SciPy, increasing onboarding conversion 8% through validated product changes. Created forecasting models with Prophet and ARIMA, improving weekly transaction-volume forecast accuracy 17%.

Full-Stack-Entwickler – Ich bin verantwortlich für die Entwicklung neuer Funktionen für Sellerlegend. Sellerlegend ist ein Verwaltungstool für Amazon-Verkäufer, das auf AWS läuft. Meine Hauptaufgaben: 1. Benutzeroberfläche entwickeln (ReactJS & CSS3) 2. API-Endpunkte erstellen (Spring Boot & MySQL) 3. Datenbank entwickeln & optimieren Ich sorge dafür, dass die Anwendung leistungsstark, benutzerfreundlich und zuverlässig bleibt.

Machine Learning, Causal Discovery, Causal Inference

Software Engineering. Analysis of Algorithms. Web Development.