产品分析 - 开发者体验，Bridge
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Product Analytics - Developer Experience, BridgeStripe · N/A
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职位描述
机器翻译我们是谁
关于 Bridge
我们正在打造一个全新的支付平台，基于稳定币构建，旨在简化全球资金流动。Bridge 通过稳定币实现更快、更便宜的支付以及无国界的美元访问。通过我们的 API，企业可以比 SWIFT 和其他仅支持法币的通道更快、更便宜地跨境收发资金。我们的虚拟账户使国际消费者和企业能够轻松访问、存储和使用美元。我们的付款基础设施使平台能够向全球任何人支付美元。我们相信数万亿美元将通过稳定币支付通道流动和结算。Bridge 正在推动这一未来加速到来。
我们有一支小团队，成员此前曾在一些全球领先的公司（Coinbase、Stripe、Square、Brex、Upstart、DoorDash、Airbnb）构建金融基础设施，他们每个人都选择 Bridge，因为他们从根本上相信稳定币将成为关键金融基础设施的一部分，从而改善全球资金流动。
你将做什么
我们正在寻找一名产品分析师加入 Bridge 的数据团队。你将负责 Bridge 客户体验的数据战略，涵盖两个紧密相关的领域：
• 支付质量——我们支付通道和产品中的交易速度、正常运行时间/可靠性、错误率以及支持工单趋势。
• 产品体验——客户如何与 Bridge 的仪表盘、引导流程和其他界面互动，以及摩擦在哪些方面让我们损失了采用率或信任。
随着业务发展，这一重点领域可能会随时间变化，我们正在寻找能够相应调整其工作范围的人——随着优先事项出现或变化，快速建立对不同产品领域的了解，创建新的分析和埋点。
这是一个高自主权的职位：你将成为你重点领域的主要数据发声者，需要识别什么重要，构建管道和分析来证明它，并推动从洞察到已交付成果的决策——并拥有真正的自由度来定义你如何实现目标。
职责
岗位职责
我们正在寻找一名产品分析师加入 Bridge 的数据团队。你将负责 Bridge 客户体验的数据战略，涵盖两个紧密相关的领域：
• 支付质量——我们支付通道和产品中的交易速度、正常运行时间/可靠性、错误率以及支持工单趋势。
• 产品体验——客户如何与 Bridge 的仪表盘、引导流程和其他界面互动，以及摩擦在哪些方面让我们损失了采用率或信任。
随着业务发展，这一重点领域可能会随时间变化，我们正在寻找能够相应调整其工作范围的人——随着优先事项出现或变化，快速建立对不同产品领域的了解，创建新的分析和埋点。
这是一个高自主权的职位：你将成为你重点领域的主要数据发声者，需要识别什么重要，构建管道和分析来证明它，并推动从洞察到已交付成果的决策——并拥有真正的自由度来定义你如何实现目标。
• 端到端负责你重点领域的数据需求：定义并完善正确的指标，构建获取这些指标的管道，并推动它们进入决策——无需大量手把手指导。
• 分析支付质量信号（延迟、正常运行时间、失败/错误率、支持工单量及主题），以识别客户在哪些方面遇到摩擦，并量化业务影响。
• 分析产品和 UX 数据（仪表盘使用情况、引导漏斗、功能采用情况），以寻找改善客户旅程的机会。
• 设计、构建和维护稳健且文档完善的数据管道和 ETL 流程，使客户体验数据易于全公司访问、信任和查询。
• 在 Databricks 中编写和维护生产级 SQL 和管道代码，工作内容通过 GitHub 进行版本控制和审查。
• 构建和维护仪表盘及自助工具，使产品、工程和支持团队能够监控客户体验指标，而无需依赖临时请求。
• 与产品、工程和支持/运营团队跨职能合作，将发现转化为具体的产品和流程改进。
• 在支付质量或产品体验中的新问题或趋势成为面向客户的问题之前，主动标记它们。
• 随着 Bridge 的产品和规模发展，持续改进你重点领域的数据质量、文档和工具。
任职要求
我们正在寻找符合该职位最低要求的人选。如果你符合这些要求，鼓励你申请。优先资格是加分项，而非要求。
最低要求
• 6 年以上数据分析师或类似分析岗位经验，最好是在支付、金融科技或高增长科技公司。
• 出色的 SQL 技能，具有在现代仓库/湖仓环境（例如 Databricks）中查询和建模数据的经验。
• 具有构建和维护数据管道及 ETL 流程的实操经验，并能将版本控制（GitHub）作为技术工作流的一部分熟练使用。
• 强大的分析和诊断能力——能够独立调查问题、识别根本原因，并将发现转化为清晰的建议。
• 具有构建仪表盘和可视化的经验，能够向技术和非技术利益相关者清晰传达洞察。
• 展现出独立工作、负责一个重点领域，并在极少监督下管理多个并行优先事项的能力。
• 强大的书面和口头沟通能力，能够向非技术受众解释技术性或数据驱动的发现。
• 具有专门分析支付数据（交易质量、正常运行时间/可靠性、支持工单趋势）或产品/UX 数据（引导、仪表盘参与度、漏斗）的经验。
• 编程经验（例如 Python），并熟悉数据处理库（例如 pandas）。
• 具有在快节奏初创公司或高增长环境中工作的经验，其中优先事项和范围会随业务变化。
以上内容由机器翻译自动生成，可能存在错误；投递前请以雇主原文为准。
查看雇主原文
职位描述
Who we are
About Bridge
We’re creating an entirely new payments platform, built with stablecoins, to simplify global money movement. Bridge enables faster, cheaper payments and borderless access to dollars via stablecoins. Through our APIs, businesses can send and receive funds across borders faster / cheaper vs. SWIFT and other fiat-only rails. Our virtual accounts enable international consumers and businesses to easily access, store and spend US dollars. Our payouts infrastructure enables platforms to disburse USD to anyone globally. We believe many trillions of dollars will move and settle through stablecoin payment rails. Bridge is pulling this future forward.
We have a small team of people who have previously built financial infrastructure at some of the world’s leading companies (Coinbase, Stripe, Square, Brex, Upstart, DoorDash, Airbnb) and each and every one of them chose Bridge because they fundamentally believe that stablecoins will be a critical piece of financial infrastructure that allows for the improvement of global money movement.
What you’ll do
We are looking for a Product Analyst to join our Data team at Bridge. You'll own the data strategy for customer experience at Bridge, spanning two closely linked areas:
• Payments quality — transaction speed, uptime/reliability, error rates, and support ticket trends across our payment rails and products.
• Product experience — how customers interact with Bridge's dashboard, onboarding flows, and other surfaces, and where friction is costing us adoption or trust.
This focus area may shift over time as the business evolves, and we're looking for someone who can adapt their scope accordingly — spinning up their knowledge of different product areas, creating new analyses and instrumentation as priorities emerge or change.
This is a high-ownership seat: you'll be the primary data voice for your focal area, expected to identify what matters, build the pipelines and analysis to prove it, and drive decisions from insight through to shipped outcomes — with real latitude to define how you get there.
Resp
岗位职责
We are looking for a Product Analyst to join our Data team at Bridge. You'll own the data strategy for customer experience at Bridge, spanning two closely linked areas:
• Payments quality — transaction speed, uptime/reliability, error rates, and support ticket trends across our payment rails and products.
• Product experience — how customers interact with Bridge's dashboard, onboarding flows, and other surfaces, and where friction is costing us adoption or trust.
This focus area may shift over time as the business evolves, and we're looking for someone who can adapt their scope accordingly — spinning up their knowledge of different product areas, creating new analyses and instrumentation as priorities emerge or change.
This is a high-ownership seat: you'll be the primary data voice for your focal area, expected to identify what matters, build the pipelines and analysis to prove it, and drive decisions from insight through to shipped outcomes — with real latitude to define how you get there.
• Own the data needs for your focal area end-to-end: define and refine the right metrics, build the pipelines to source them, and drive them into decisions — without needing significant hand-holding.
• Analyze payments quality signals (latency, uptime, failure/error rates, support ticket volume and themes) to identify where customers are experiencing friction and quantify the business impact.
• Analyze product and UX data (dashboard usage, onboarding funnels, feature adoption) to find opportunities to improve the customer journey.
• Design, build, and maintain robust, well-documented data pipelines and ETL processes that make customer experience data easy to access, trust, and query across the company.
• Write and maintain production-quality SQL and pipeline code in Databricks, with work version-controlled and reviewed via GitHub.
• Build and maintain dashboards and self-serve tools that let Product, Engineering, and Support teams monitor customer experience metrics without depending on ad hoc requests.
• Partner cross-functionally with Product, Engineering, and Support/Operations to translate findings into concrete product and process improvements.
• Proactively flag emerging issues or trends in payments quality or product experience before they become customer-facing problems.
• Continuously improve data quality, documentation, and tooling for your focal area as Bridge's product and scale evolve.
任职要求
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
• 6+ years of experience as a data analyst or in a similar analytics role, ideally at a payments, fintech, or high-growth technology company.
• Excellent SQL skills, with experience querying and modeling data in a modern warehouse/lakehouse environment (e.g., Databricks).
• Hands-on experience building and maintaining data pipelines and ETL processes, and comfort working with version control (GitHub) as part of a technical workflow.
• Strong analytical and diagnostic skills — able to independently investigate a problem, identify root cause, and turn findings into a clear recommendation.
• Experience building dashboards and visualizations that communicate insights clearly to both technical and non-technical stakeholders.
• Demonstrated ability to work independently, take ownership of a focal area, and manage multiple concurrent priorities with minimal oversight.
• Strong written and verbal communication skills, with the ability to explain technical or data-driven findings to non-technical audiences.
• Experience analyzing payments data specifically (transaction quality, uptime/reliability, support ticket trends) or product/UX data (onboarding, dashboard engagement, funnels).
• Programming experience (e.g., Python) and familiarity with data manipulation libraries (e.g., pandas).
• Experience working in a fast-paced startup or high-growth environment where priorities and scope shift with the business.