Data & Operations Analyst | SQL • Python • Excel • Tableau | BI • Data Quality • Process Improvement

San Diego, CA · LinkedIn · Email

I turn messy operational data and workflows into trusted metrics, clear reporting, and decision-ready analysis. My work focuses on the full analyst lifecycle: framing the business question, validating the data, defining defensible metrics, building reproducible SQL/Python analysis, and communicating what the evidence supports — and what it does not.

My broader operations background spans automotive business operations, independent logistics, and public-sector procurement support, giving me practical context for workflow, documentation, exceptions, and execution.

Real public data · SQL · Python · DuckDB · Excel · Dashboarding · Data Quality · Cohort Analysis · Executive Communication

End-to-end operations analysis of 714,925 real City of San Diego Get It Done service-request records to identify where active inventory is concentrated, how old it is, how duplicates and record structure affect interpretation, and where leadership should investigate first.

• Audited three official extracts and built a reproducible SQL/Python analysis pipeline with explicit metric definitions and privacy-safe outputs.
• Found 81,359 active requests at the Aug. 9, 2026 snapshot; 76.1% were older than 90 days and 51.0% older than one year.
• Tested duplicate handling, cohort bias, geography, submission channel, taxonomy changes, and priority-score sensitivity instead of assuming the first result was correct.
• Delivered an executive dashboard, six-sheet Excel workbook, one-page decision memo, data-quality report, automated tests, and strict claim verification.

Repository · Dashboard · SQL · Excel · Executive Memo

Operations analytics · SQL · Python · DuckDB · Data Quality · Dashboards · Testing

Synthetic healthcare operations case study across prior-authorization readiness, provider onboarding, and diagnostic/lab revenue-cycle readiness.

• Built structured workflows that surface blockers, aging, ownership, readiness, and next-action queues.
• Created a runnable SQL portfolio answering eight operational business questions.
• Added explicit data-quality checks, metric definitions, automated tests, executive reporting, and an AI quality evaluation lab.
• Uses synthetic/mock data only — no PHI or real patient, provider, payer, or claims data.

Product Demo · Analytics App · SQL Evidence · Implementation Case

Research analytics · Python · Validation · Robustness · Risk · Reproducibility

A synthetic research lab designed around disciplined evaluation rather than trading claims.

• Separates in-sample selection from held-out evaluation.
• Uses walk-forward validation, Monte Carlo robustness, regime analysis, transaction-cost sensitivity, and stress diagnostics.
• Produces KPI reporting and a self-contained executive research dashboard.
• Runs on synthetic data by default and makes no live-trading or performance guarantees.

Analytics: SQL · BigQuery · Python · pandas · Excel · Tableau · DuckDB · KPI design · data validation · operational reporting

Delivery: Streamlit · FastAPI · Git/GitHub · pytest · CI · documentation · reproducible workflows

Business / Operations: workflow mapping · issue and discrepancy analysis · process improvement · stakeholder reporting · requirements thinking

• Associate degrees in Accounting, Economics, and Business Administration — Southwestern College
• Google Data Analytics Professional Certificate — completed 2026
• Bilingual: English / Spanish

Data Analyst · BI / Reporting Analyst · Operations Analyst · Data Quality Analyst · Implementation Analyst · Business Systems / Process Analyst

San Diego-area and remote opportunities.