Applied Analytics
End-to-end analysis and decision support for real datasets and operational workflows.
- → Predictive maintenance + risk monitoring
- → Fraud detection + threshold trade-offs
- → EDA across large sales datasets
I turn complex datasets into executive-ready dashboards, risk signals, and decision support—using Python, SQL, and Power BI.
Applied analytics work and leadership — optimized for fast scanning.
End-to-end analysis and decision support for real datasets and operational workflows.
KPI storytelling with dashboards, drilldowns, and decision-ready reporting.
Team coordination, event execution, and community leadership.
Three high-impact case studies
Decision-support workflow that converts sensor signals into CCME-WQI scores, risk tiers, and anomaly alerts; deployed as API + web interface.
Fraud analytics solution with threshold tuning to balance detection performance and customer experience.
End-to-end BI solution: MySQL data source + transformations + DAX measures + Power BI dashboard for global expansion insights.
A focused mix of analytics, BI, modeling, and delivery tools I use to turn data into decisions.
I work across data analysis, dashboarding, and predictive modeling to support business decisions. My approach combines technical execution with clear reporting and stakeholder-friendly storytelling.
Power BI, dashboards, DAX, KPI reporting.
EDA, trend analysis, segmentation with Python/R.
Predictive modeling, evaluation, explainability.
FastAPI, Streamlit, MySQL, Jupyter.
Contact
Open to Data Analyst roles, BI work, analytics projects, and meaningful collaboration. I respond best to messages that include the role or project context.
Typical response time: 24–48 hours.