Capabilities
Skills & Tools
A recruiter-friendly breakdown of my analytics toolkit — from BI dashboards and EDA to predictive modeling and deployed data apps.
Analytics & BI
Translating raw data into executive-ready dashboards and KPI frameworks.
Multi-page dashboards, drill-downs, bookmarks
Measures, calculated columns, time intelligence
Metric definitions, scorecards, executive views
Narrative structure, visual hierarchy, stakeholder framing
Data Analysis
Exploratory analysis, trend discovery, and insight generation across large datasets.
Pandas, NumPy, Matplotlib, Seaborn
ggplot2, dplyr, time series
Distributions, correlations, outlier detection
Joins, CTEs, window functions, views
Applied ML
Predictive modeling pipelines with explainability and business-aligned evaluation.
Scikit-learn, XGBoost, cross-validation
TensorFlow/Keras, neural architectures
SHAP, Integrated Gradients, feature importance
PR-AUC, ROC, threshold tuning, confusion matrix
Tools & Delivery
End-to-end deployment of analytics apps and APIs with clean documentation.
REST endpoints, Swagger docs, async routes
Interactive dashboards, model UIs
Notebook-driven analysis and reporting
Pivot tables, VLOOKUP, data validation
Core Tools
Everything I reach for day-to-day
Professional Strengths
The non-technical side that makes analytics land
Want to see these skills in action?
Explore the case studies for real dashboards, analysis notebooks, and deployed workflows.