Turning raw data into decisions — from Azure pipelines to Power BI dashboards, GA4 tracking to published ML research.
I'm a Data Analyst with 2+ years of experience building end-to-end data solutions — from architecting Azure ETL pipelines to shipping production-ready BI dashboards and implementing server-side tracking at scale.
At Kilowott, I work at the intersection of engineering and strategy — being the person who connects technical implementation with real business questions. Whether that's debugging a tracking gap that's skewing conversion data, or sitting with a marketing team to understand what they actually need from a report.
Beyond analytics, I have a foundation in NLP and deep learning from published academic research — my work on cryptocurrency price prediction was published in Springer Nature (2025).
Architected and maintained end-to-end ETL pipelines integrating marketing, sales, and email datasets from Azure into Power BI — enabling real-time decision-making for the marketing team across 5+ data sources.
Implemented server-side and browser-side GTM tracking across client websites, eliminating data gaps caused by ad-blockers and browser restrictions — achieving 100% event capture accuracy with validated data quality.
Delivered 40+ interactive dashboards tracking campaign KPIs, funnel metrics, and conversion trends across Google, Meta, Snapchat, and Klaviyo — enabling centralized cross-channel performance visibility.
Established data validation frameworks and quality assurance protocols ensuring integrity of all ingested data before visualization, reducing reporting discrepancies by an estimated 30%.
Published as a final-year undergraduate, this research demonstrates advanced applied ML skills. Vol. 6, Article No. 67.
Open to full-time roles, freelance projects, or just a good conversation about data.