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David Alvarado
Junior Business Analyst specializing in data analytics and BI
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Analytics candidate with insurance domain experience at Chubb, combining strong SQL/Python data engineering for claims reporting with business-facing metric design in Power BI. Also built an MLB game outcome predictor that beat Vegas implied probabilities using public data, showing strong product thinking and applied modeling ability beyond standard BI work.
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Key Strengths
- SQL-based data cleaning and transformation of messy multi-source claims data
- Strong data quality validation with stepwise checks and discrepancy thresholds
- Debugging complex joins and pipeline issues through staged reconciliation
- Performance optimization for reporting tables via partitioning
- Built reproducible Python reporting pipeline using Snowflake and pandas
- Reduced manual reporting time by 30%
- Dashboard enablement for leadership through Power BI automation
- Thoughtful metric design with edge-case handling for claims reopening rate
- Drove stakeholder adoption by embedding metrics and definitions into existing dashboards
- End-to-end analytics ownership from framing to impact measurement
- Applied rigorous model evaluation using ROC-AUC and cross-season validation
- Built MLB prediction model outperforming Vegas implied baseline (0.629 vs 0.570 ROC-AUC)
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