Data Analyst · Oct 2023 – present

Nerevu Group

Nerevu Group LLC · Peoria, Illinois · worked remotely from Portland, OR

Production pipelines, financial data integration, model evaluation, dashboards and published reports, across internal tools and client projects.

18pipeline steps, sole programmer

~1,000tests in CI

30 → 1minutes of lead prep

What I worked on

• Government contracting pipeline
• CI & testing
• Financial data integration
• Hiring funnel analysis
• ATS & CRM dashboards
• Classifier & LLM evaluation
• Reports & infographics

⚙️Government contracting pipeline

I was the sole programmer on an 18-step Python, PostgreSQL and Airtable pipeline on Heroku that turns raw government contracting data into ready-to-use leads for Nerevu's internal team.

CollectREST APIs, web scraping, PDF and XFA extraction

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EnrichLLM summarization, graded by an automated quality scorer

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StorePostgreSQL, synced to Airtable for the team

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ReportReady-to-use leads in about a minute

⏱️Lead prep time

Minutes to prepare one lead.

🧪CI & testing: fixes that stay fixed

I set up the project's error logging and its first CI, which grew to about 1,000 tests. Every production error followed the same loop, so a problem couldn't quietly come back.

1 · Error loggedProduction error is captured automatically

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2 · IssueIt becomes a tracked issue

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3 · TestA test that recreates it is written first

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4 · FixThe fix ships with that test pinned in CI

🏦Financial data integration

Kept a mortgage lending client's production SQL Server and SSIS integration running every night.

• Stored procedures for the nightly loads
• Dynamic table-comparison scripts across 268-column loan tables, reconciling each load against source
• SQL Server Agent job monitoring with SQL and SMS alerts when a load failed

🔻Hiring funnel analysis

Analyzed Nerevu's internal 1,000+ applicant hiring funnel stage by stage, and modeled which candidates advance to the next stage.

📊ATS & CRM dashboards

Customized Nerevu's internal applicant tracking system (ATS) and CRM dashboards.

🔍Classifier & LLM evaluation

• Research on people: designed the accuracy tests that decided whether a name-based demographic classifier was fit to report on in a market disparity study. It replaced a 30-minute manual review per record.
• LLM quality: wrote an automated scorer that grades LLM output inside the production pipeline, before anything downstream uses it.

📝Reports & infographics

Produced the infographics and charts, and edited the final documents, for two government reports:

• Municipal data governance study
• Market disparity study, with colorblind-safe visuals and an executive recommendations table

🧰Tools

• Python
• PostgreSQL
• SQL Server (T-SQL)
• SSIS
• SQL Server Agent
• Airtable
• Heroku
• REST APIs
• Web scraping
• LLMs
• GitHub Actions
• pytest

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