I bring structure to raw information—identifying patterns, trends, and opportunities that drive smarter decisions. Whether it's through Python, Excel, or Power BI dashboards, I leverage the right tools to explore, analyze, and visualize data in ways that are both informative and intuitive. From cleaning and wrangling data to building models and designing visual narratives, I aim to make data not just accessible, but impactful.

I build intelligent systems that learn from data and uncover the underlying patterns that drive real-world outcomes. My expertise lies in developing machine learning models and mathematical system models that not only make accurate predictions but also offer deep insights into complex systems. From supervised learning and classification to unsupervised clustering and time-series forecasting, I apply the right algorithms to solve problems across diverse domains. I complement model development with rigorous evaluation, feature engineering, and interpretability to ensure models are both effective and trustworthy. With a strong foundation in statistics, linear algebra, and optimization, I bring a scientific approach to data-driven decision-making.

I design and build efficient ETL (Extract, Transform, Load) processes that move data seamlessly from source to insight. With hands-on experience in developing robust data pipelines, I specialize in integrating diverse data sources, automating workflows, and ensuring high data quality and reliability at every stage. My approach emphasizes scalability, performance optimization, and maintainability—whether working with SQL-based systems, dbt, or cloud-native tools. From data ingestion to transformation logic, I focus on creating pipelines that support timely, accurate analytics and empower data-driven decision-making.