— Graduated in Computer Engineering with a strong academic and project-based foundation in data science, data engineering, and analytics-driven problem solving. — Built end-to-end machine learning solutions, covering the full lifecycle from data collection and preprocessing to model deployment and performance monitoring. — Developed a multilingual hate speech detection system, working with noisy, imbalanced text data across multiple languages and applying NLP techniques for real-world content moderation. — Created a face-recognition attendance platform, integrating computer vision with backend data pipelines to handle streaming video input and store structured attendance logs. — Holds IBM Data Science Professional Certificate, demonstrating practical knowledge in Python, SQL, data visualization, exploratory analysis, and supervised/unsupervised learning. — Proficient in Python (pandas, NumPy, scikit-learn, TensorFlow), SQL (window functions, joins, aggregations), and statistical methods (hypothesis testing, A/B testing, regression diagnostics). — Experienced in data wrangling, feature engineering, and handling missing or inconsistent data from multiple sources (APIs, relational databases, CSV/JSON files). — Passionate about working with diverse, large-scale, real-world data to extract actionable insights and support evidence-based decision-making. — Actively seeking a professional data science or data engineering role where I can contribute to robust data architectures, scalable pipelines, and impactful analytical products.