数据科学家—欺诈
Data Scientist - Fraud
我们相信，人们与财务的互动方式将在未来几年得到显著改善。我们致力于通过构建数千名开发者用来创建自己产品的工具和体验，推动这一变革。Plaid 为数以百万计的人们依赖的工具提供支持，帮助他们过上更健康的财务生活。我们与 Venmo、SoFi、多家财富 500 强公司以及许多大型银行合作，让人们能够轻松地将财务账户连接到他们想要使用的应用和服务。Plaid 的网络覆盖美国、加拿大、英国和欧洲的 12,000 家金融机构。公司成立于 2013 年，总部位于旧金山，并在纽约、西雅图、华盛顿特区、罗利、伦敦和阿姆斯特丹设有办事处。
我们是 Plaid 风险部门中的数据团队。我们构建用于 Plaid 风险检测产品的机器学习系统，利用 Plaid 的网络数据来识别并防止欺诈行为的发生。我们的团队负责整个机器学习生命周期，从特征管道和模型训练到生产服务和监控，确保我们的系统可靠、可扩展，并能支持数百位客户和数据合作伙伴。
作为风险数据团队的数据科学家，你将分析客户和网络流量，了解 Plaid Protect 在各种使用场景和客户群体中的表现。你将构建仪表板和指标，提供清晰、共享的产品性能视图，运行回测以评估性能并识别高影响力的规则和模型策略，生成支持客户增长和扩展的洞察。你还将设计可扩展的数据模型和模式，以实现可靠的分析和报告，同时与产品和工程团队紧密合作，设计和分析新客户功能的实验。
职责：
- 在产品分析、机器学习、风险和欺诈的交汇点工作，发现提升产品性能的洞察。
- 负责影响产品策略和决策的指标、仪表板和实验。
要求：
- 3-5 年相关经验，其中至少 2-3 年在产品分析、实验或数据驱动产品方面有深入经验。
- 精通 SQL 和 Python，有分析复杂数据集并将其转化为行动见解的经验。
- 有产品分析的实际经验
查看英文原文
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners.
As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features.
Responsibilities:
- Work at the intersection of product analytics, machine learning, and fraud and risk to uncover insights that improve product performance.
- Own the metrics, dashboards, and experiments that inform product strategy and decision-making.
Qualifications:
- 3–5 years of relevant experience, including at least 2–3 years working extensively with product analytics, experimentation, or data-driven products.
- Strong proficiency in SQL and Python, with experience analyzing complex datasets and translating insights into action.
- Hands-on experience with product analytics, experimentation, and/or backtesting methodologies.
- Experience building and maintaining dashboards, reporting frameworks, and core product metrics.
- Strong communication and stakeholder management skills, with the ability to translate complex analyses into clear, actionable insights for technical and non-technical audiences.
Nice-to-Have:
- Experience in fraud/risk domains
- Experience with developing ML models
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here https://plaid.com/legal/#candidate-privacy-notice.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.