I transform complex data into actionable insights and build scalable data solutions. Passionate about machine learning, data engineering, and creating impact through analytics.
I worked as a Data Engineer with 2+ years of experience at leading companies including Shell, Bosch, and Deloitte. I specialize in building scalable data pipelines, machine learning models, and analytics solutions that drive business impact.
Currently pursuing MS in Data Science at Arizona State University, I combine academic rigor with real-world experience to solve complex data challenges and create innovative solutions.
Data loading time reduction
Years Industry Experience
Faster processing times achieved
Spearheaded the transition project at Shell, revamping legacy dashboards and conducting rigorous testing to ensure zero data discrepancies and maintain data integrity across platforms.
Developed a Python and Streamlit-based recommendation system at Bosch that slashed delivery times by 12% through improved route selection and provider matching.
Orchestrated complete HR sentiment analysis using VADER framework and Power BI, delivering insights that improved employee satisfaction scores by 8% within six months.
Engineered an ASP.NET Core and SQL Server web application at Deloitte that automated tax data uploads, leading to 30% faster processing times and enhanced data accuracy.
Building an intelligent trading system that uses LLMs to generate algorithmic strategies, backtests them on historical data, and provides comprehensive performance analytics with natural language explanations.
Delivered Flutter application with 3D viewport for live multi-camera stitching using AWS infrastructure, slashing testing time by 30% in collaborative Samsung R&D project.
I'm always interested in new opportunities and exciting projects. Feel free to reach out!