• 📊 Financial Analyst (FP&A) with 4+ years in banking and payments: Wells Fargo and Mastercard
• 🎓 M.S. in Business Analytics, Sacred Heart University, Connecticut
• 🔍 I turn month-end pain into working tools: journal screening, currency bridges, feed validation, and close analytics
• 📈 Built financial models supporting $180M+ budgets, automated 20+ hours/month of manual reporting, and analyzed 12M+ transaction records with SQL
• 🧪 My rule for every repo below: every number is measured by a script in the repo, never asserted
• 📫 Reach me at nvanithanallamothu@gmail.com

Every metric below is generated by a benchmark script inside the repo, on stated hardware, and can be rerun.

GL journal screener that reads every entry instead of sampling: Benford's law per preparer, split detection, round numbers, off-hours postings, rare account pairs. 1M journals in 13s • 95.7% of seeded anomalies flagged, only 0.4% of clean entries touched • 95% test coverage

Constant-currency engine that splits multi-entity growth into scope, organic, and FX impact with a bridge that ties to reported figures, no plug line. Max residual 0.000001 at 1,000 entities • randomized tie-out property test • executive Excel + Power BI exports • 96% coverage

Fail-closed firewall for inbound transaction feeds: manifest control totals in integer cents, SHA-256 duplicate fingerprints, robust outlier checks, S3/MinIO landing zones. 25k rows/s in a flat 257 MB from 1M to 3M rows • machine-readable quarantine verdicts • 95% coverage

The month-end close as a dependency DAG: from-scratch Critical Path Method, append-only audit event log, bottleneck analytics. 10,000-task analysis in 4s • CPM verified on 300 randomized DAGs • 39-task banking close template included • 97% coverage