truv - by Checkr - Lead Product Manager, Data Sources
Requirements
• 7+ years in product management, with significant time in data, ML/AI, fintech, or verification / identity platforms. • Demonstrated experience owning a data-intensive product — document understanding, OCR, financial data aggregation, fraud, or similar — at meaningful scale. • Strong technical fluency. You can reason about extraction models, API tradeoffs, and pipeline architecture without needing to be hand-held by engineering. • Track record of driving SLA / reliability outcomes — not just shipping features, but moving the numbers that matter. • Experience working with regulated industries (mortgage, lending, government) is a strong plus. GSE / FCRA / FNMA / FHLMC familiarity especially. • Strong written communication. You write the 1-pagers and specs that align the team. • Customer obsession. You spend real time with users and let what you learn shape the roadmap. • Worked on a verification or KYC/KYB product used by lenders. • Comfortable shipping in a startup environment where ambiguity is high and the bar moves up.
Responsibilities
• Set the multi-quarter roadmap for Data Sources across docs, fraud, and aggregation; align it with revenue, client commitments, and platform-level constraints. • Write tight specs and 1-pagers; partner with Eng and Data Science to scope, build, and ship. • Talk to clients (mortgage lenders, government agencies, tenant screeners) weekly; turn their feedback into prioritized roadmap. • Own the metrics — parse accuracy, fraud catch rate, bank connection success, SLA hit rate — and the rituals that drive them up. • Lead and mentor PMs and engineers on the team; raise the bar on shipping speed and quality. • Represent Truv's data sources story externally (sales calls, conferences, partner reviews). • ## What You'll Own: • 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 • Set the multi-quarter roadmap for Data Sources across docs, fraud, and aggregation; align it with revenue, client commitments, and platform-level constraints. • Write tight specs and 1-pagers; partner with Eng and Data Science to scope, build, and ship. • Talk to clients (mortgage lenders, government agencies, tenant screeners) weekly; turn their feedback into prioritized roadmap. • Own the metrics — parse accuracy, fraud catch rate, bank connection success, SLA hit rate — and the rituals that drive them up. • Lead and mentor PMs and engineers on the team; raise the bar on shipping speed and quality. • Represent Truv's data sources story externally (sales calls, conferences, partner reviews).
Benefits
• High leverage. Data sources are upstream of every Truv product. Improvements compound across mortgage, tenant screening, government, and any new vertical we enter. • Mature platform, room to push. Truv ships in production with major mortgage lenders today. Your job is to take a working platform and make it best-in-class. • Real complexity. Document parsing, fraud, and bank aggregation each have multi-year roadmaps. You'll get to operate across all three as one cohesive system. • Tight team. You'll work directly with senior leadership, the engineering teams that own these surfaces, and the largest clients in the space.
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