Lead Product Manager, Data Sources

Document parsing - Drive the roadmap for parsing income and document types. Improve accuracy, reduce manual review, and shorten time-to-report. Partner with Data Science on extraction models and with Ops on the human-in-the-loop pipeline.

Scaling document types - Expand the catalog of supported document types beyond the current set. Identify the highest-impact additions (by use case, client demand, and revenue impact), prioritize the rollout, and own the end-to-end product surface from upload to verified output.

Fraud detection - Define and ship the fraud signal layer across data sources — document tampering detection, deposit-pattern anomalies, identity mismatches, and synthetic income flags. Balance precision and recall against client-specific risk tolerances, and build the configuration surface for clients to tune.

Optimizing and scaling bank aggregation - Lead the Truv's bank aggregation product, connection success rates, refresh cadence, transaction enrichment, and coverage. Reduce drop-off, improve match rates, and expand FI coverage where it matters most for mortgage and tenant use cases.

SLAs and reliability - Set, instrument, and defend SLAs across every data source: time-to-first-data, time-to-completed-report, refresh success rate, document parse accuracy, and bank connection uptime. Drive the dashboards, alerts, and review cadence that make these visible — and the engineering work that makes them improve