远程工作雷达

数据源负责人产品经理

Lead Product Manager, Data Sources

职能支持全球可投
公司truv
薪资未公开
工作地点Remote
地域资格全球可投
时区要求无特别要求
用工类型未标注
发布时间未知
数据来源Lever
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全球可投:该职位未限制候选人所在地区。仍需注意薪资可能按地区折算,以及实际签约方式(正式雇佣 / 独立合同)。

关于 Truv:

Truv 正在构建支撑消费者授权收入、就业、身份和资产验证的基础设施层。我们帮助贷款机构、金融科技公司和金融机构做出更快、更准确的决策,同时提供无缝的消费者体验。

随着我们数据网络和验证能力的持续扩展,我们正在寻找一位数据源产品经理负责人,负责并扩展我们的数据源平台——这是支撑 Truv 产品中文档摄入、欺诈检测、银行连接和数据可靠性的重要基础。

职位描述:

我们正在寻找一位经验丰富的数据源产品经理,负责执行路线图及收集、处理和验证消费者金融数据的系统执行。

该职位位于数据基础设施、机器学习、欺诈预防和金融数据聚合的交汇点。您将负责构建可扩展的能力,以提升 Truv 平台上的数据覆盖范围、质量、可靠性和信任度。

您将与工程、数据科学、欺诈、运营、客户成功和 GTM 团队紧密合作,交付直接影响转化率、客户满意度和运营效率的产品。

您将负责以下内容:

文档解析 - 主导收入和文档类型解析的路线图。提高准确性,减少人工审核,缩短报告时间。与数据科学团队合作开发提取模型,并与运营团队合作建立人机协作流程。

扩展文档类型 - 将支持的文档类型目录扩展到当前支持的范围之外。识别最具影响力的新增类型(根据用例、客户需求和收入影响),优先安排上线,并负责从上传到验证输出的全流程产品设计。

欺诈检测 - 定义并推出跨数据源的欺诈信号层——包括文档篡改检测、存款模式异常、身份不匹配和合成收入标志。在客户特定的风险容忍度范围内平衡精确率和召回率,并为客户构建配置界面进行调整。

优化和扩展银行聚合 - 领导 Truv 的银行聚合产品,包括连接成功率、刷新频率、交易丰富化和覆盖范围。降低流失率,提高匹配率,并在抵押贷款和租户使用场景中最重要的地方扩展金融机构覆盖范围。

SLA 和可靠性 - 在每个数据源上设定、监控并维护 SLA:首次数据到达时间、时间

查看英文原文

About Truv:

Truv is building the infrastructure layer that powers consumer-permissioned income, employment, identity, and asset verification. We help lenders, fintechs, and financial institutions make faster, more accurate decisions while delivering a seamless consumer experience.

As we continue to expand our data network and verification capabilities, we're looking for a Lead Product Manager to own and scale our Data Sources platform—the foundation that powers document ingestion, fraud detection, bank connectivity, and data reliability across Truv products.

About the Job:

We are seeking an experienced Lead Product Manager, Data Sources to own the execution of the roadmap, and execution for the systems that collect, process, and validate consumer financial data.

This role sits at the intersection of data infrastructure, machine learning, fraud prevention, and financial data aggregation. You will be responsible for building scalable capabilities that improve data coverage, quality, reliability, and trust across Truv's platform.

You will work closely with Engineering, Data Science, Fraud, Operations, Customer Success, and GTM teams to deliver products that directly impact conversion, customer satisfaction, and operational efficiency.

We are an equal-opportunity employer committed to diversity. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

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

What You'll Do

  • 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).

Who You Are

  • 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.

Why this role:

  • 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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