I work on data problems close to operations. The goal is simple: shorten the loop from “question” to “decision.” I ship small, reliable tools—spreadsheets, SQL models, and lightweight scripts—that people can use today.

Current — Facility Support Manager, GBA Associates (DHHQ).
Own the facility-support workflow end to end (intake → triage → vendor dispatch → close out) and turn ticket data into decisions. Built:

  • An Excel/VBA multi-criteria search across large project and work order lists (lookup time dropped from minutes to seconds).
  • Power Query pipelines that consolidate multi-year exports and vendor files into one clean model.
  • Compact dashboards for SLA and volume trends, aging, and recurring issues.

Previously — Pro Sales, Lowe’s.
Managed contractor accounts, kept inventory and procurement moving, and shipped the simplest solution people would actually use.

Education

  • B.S., Management Information Systems — George Mason University (2021–2023)
  • A.S., Business Administration — Northern Virginia Community College (2019–2021)

How I work

  • Start with a Decision Brief. What decision, by whom, by when, with what success metric and constraints.
  • Baseline first, then improve. Establish the current number, define “good enough,” and iterate toward it.
  • Data hygiene before charts. Pin down source of truth, keys, grains, and definitions. Keep a short data dictionary.
  • Make it refreshable. One click or one query to refresh (Power Query, SQL views, or parameterized extracts).
  • Short feedback loops. Ship a rough cut early, demo, collect edge cases, and fold them back in weekly.
  • Explainability over cleverness. Prefer simple, testable logic with checks and back tests.
  • Clean hand off. A README, owner, refresh steps, and a rollback plan.

What I can help with

  • KPIs and dashboards. Translate goals into measurable metrics and build lightweight dashboards in Excel / Power Query / SQL / Tableau.
  • Data cleaning and modeling. De-dupe, standardize, normalize dates, and build tidy staging tables or star-schema views.
  • Operational analytics. SLA tracking, cohort and retention, churn risk, simple forecasting.
  • Automation of ad hoc work. Refreshable pipelines; Excel + VBA utilities for bulk lookups and exports.
  • Decision support. One-page memos with context, options, trade-offs, recommendation, and next steps.
  • Enablement. Short docs and templates so the team can maintain and extend the work.

Selected work

Tools I reach for

SQL (MySQL/SSMS) Excel & VBA Power Query Tableau Power BI (basic) Python (pandas) R (tidyverse) Jupyter Git/GitHub LINGO NumPy scikit-learn Matplotlib Seaborn ggplot2

Milestones

  • 2025
    Google Data Analytics Professional Certificate — May 2025
    Coursework across cleaning, analysis, visualization, and practical stakeholder communication.
  • 2025
    Facility Support Manager — GBA Associates @ DHHQ (Mar 2025–present)
    Workflow ownership, vendor coordination, and ops reporting. Shipped Excel/VBA search, Power Query consolidation, and performance dashboards.
  • 2022–2025
    Pro Sales Associate — Lowe’s
    Managed contractor accounts, improved procurement flows, and delivered fast solutions.
  • 2021–2023
    B.S., Management Information Systems — George Mason University
  • 2019–2021
    A.S., Business Administration — Northern Virginia Community College

Now / Next

Now

  • Evaluation checklists — leakage, drift, fairness, and data-quality gates in PRs; quick sampling checks before release.
  • Decision-first write ups — one pager per analysis: decision → baseline → cost of error → recommendation → risks and next steps; link to a reproducible notebook.
  • Decision-quality metrics — calibration, lift vs. current policy, expected value and cost curves, time to insight.
  • From ad hoc to repeatable — turn scripts into refreshable pipelines; document data owners, keys, and SLAs.

Next

  • Lightweight monitoring — freshness, volume, and schema checks with simple alerts and a short runbook.
  • Human in the loop — review queue for borderline predictions; thresholds and escalation rules; feedback loop for retraining.
  • Postmortems & playbooks — tight templates, common failure modes, rollback and verify checklist.
  • Data contracts & validation — schema constraints, allowed ranges, de-dupe keys, and backfill policy.

Say hello

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