远程工作雷达

欺诈模式分析师

Fraud Patterns Analyst

职能支持限定地区(需当地身份)
公司Stripe
薪资未公开
工作地点US-Remote
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2026-05-26
数据来源Greenhouse
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注意地域限制:该职位明确限定在 US-Remote 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

我们是谁

关于 Stripe

Stripe 是一家为 businesses 提供金融基础设施的平台。数以百万计的公司——从全球最大的企业到最具雄心的初创公司——都使用 Stripe 来接受支付、增长收入并加速新的商业机会。我们的使命是提升互联网的 GDP,而我们面前还有大量工作要做。这意味着你有机会在职业生涯中做最重要的工作,同时让全球经济触手可及。

关于团队

风险运营团队正在寻找一位经验丰富的欺诈分析师加入一个行业领先的全球欺诈运营团队。该职位负责编写和维护欺诈规则集以防止交易欺诈,进行数据分析以识别和缓解欺诈攻击,同时尽量减少对用户的影响,并与欺诈、运营和产品相关方协作,主动实施欺诈策略和控制措施。他们应深入了解欺诈模式和类型,具备高级 SQL 技能,强大的分析能力,并有编写和管理欺诈规则集的经验。

你将负责的工作

你知道吗,全球 GDP 中只有约 4% 来自互联网商务?在 Stripe,我们认为这代表着一个几乎无限的创新、创造力和全球繁荣的未来。虽然全球在线经济的前景显而易见,但并不意味着没有重大风险。每天,不法分子都在破坏互联网的信任与安全,并增加在线业务的准入门槛。在我们能够完全实现全球互联网经济的潜力之前,我们必须首先解决欺诈问题的迅速增长。

我们正在寻找一位热衷于打击欺诈、识别新趋势和类型、进行复杂数据分析,并与欺诈领域的同行和合作伙伴协作的人。该职位将与产品、工程、数据科学和运营等跨职能相关方紧密合作,以识别和缓解来自复杂分布式交易欺诈攻击的风险。

该职位的合适候选人需要至少五年使用 SQL 进行高级数据分析的经验,最好是在电商、支付或加密货币领域的欺诈领域。候选人应有编写、维护和分析复杂欺诈规则集的经验,并有成功案例。

查看英文原文

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world's largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Risk Operations team is looking for an experienced fraud analyst to join an industry-leading global fraud operations team. This position is responsible for writing and maintaining fraud rulesets to prevent transaction fraud, conducting data analysis to identify and mitigate fraud attacks, while minimizing impact to users, and working collaboratively with fraud, operations, and product stakeholders to proactively implement fraud strategies and controls. They should have a deep understanding of fraud patterns and typologies, advanced SQL proficiency, strong analytical abilities, and experience writing and managing fraud rulesets.

What you'll do

Did you know that only around 4% of the world's GDP comes from internet commerce? At Stripe, we believe that this represents a future with almost limitless potential for innovation, creativity, and global prosperity. While the promise of a global online economy is palpable, it doesn't come without significant risk. Each day, bad actors disrupt the trust and safety of the internet and increase the barrier of entry for online businesses. Before we can fully realize the potential of a global internet economy, we must first address the burgeoning problem of fraud.

We are looking for someone passionate about fighting fraud, identifying new trends and typologies, conducting complex data analysis, and working collaboratively with peers and partners in the fraud space. This position works closely with cross-functional stakeholders across product, engineering, data science, and operations to identify and mitigate risk from complex, distributed transaction fraud attacks.

The right candidate for this role will have a minimum of five years' experience conducting advanced data analysis using SQL, preferably within the fraud space across e-commerce, payments, or cryptocurrency. Candidates should have experience writing, maintaining, and analyzing complex fraud rulesets and demonstrated success minimizing fraud losses along with impacts to users. Candidates should also have experience working closely with product teams to implement risk controls and demonstrate a deep understanding of fraud typologies, controls, and ability to mitigate fraud risk.

Responsibilities

  • Build and maintain fraud rulesets to prevent transaction-level fraud losses, including ongoing monitoring and measurements of precision and recall
  • Conduct advanced data analysis of structured and unstructured data sets to proactively identify emerging fraud attacks impacting Stripe and its users
  • Collaborate closely with product, risk, and operations teams to proactively identify and mitigate fraud exposure
  • Investigate, conduct root cause analysis, and deploy remediations to prevent future complex and distributed fraud attacks
  • Investigate and take action against anomalous clusters of transactions based on account activity, processing volume, or other risk indicators while minimizing negative impacts to Stripe users
  • Respond to incidents involving complex fraud schemes to quickly mitigate exposure to Stripe, its users, and financial partners
  • Utilize analytics to identify and implement initiatives to automate manual processes and workload across the organization
  • Create visualizations, dashboards, and queries to drive visibility and oversight into impact, performance, loss risks, and user experience
  • Utilize Stripe tools and systems to enable systematic actioning of fraudulent merchants, maintaining an extremely high level of accuracy to prevent negative user experience

Who you are

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

  • A minimum of five years of experience conducting advanced data analysis and managing transaction fraud rulesets
  • Advanced-level proficiency in SQL
  • Experience working closely with modeling, data science, and intelligence stakeholders to implement automatic and scaled controls and processes
  • Experience creating data visualizations and dashboards and presenting findings to technical and non-technical audiences, including senior leadership
  • The ability to drive execution on projects working in a heavily cross-functional environment
  • Creativity, a team-focused mentality, and effective problem-solving skills
  • The ability and desire to question the status quo
  • The ability to approach challenges from a user perspective while being pragmatic and solutions-oriented

Preferred qualifications

  • Fraud experience in payments, e-commerce, fintechs, or cryptocurrency mitigating digital and card-not-present fraud
  • Experience investigating and mitigating card testing and account takeover attacks
  • Proficiency in Splunk, Python, Tableau, or other data visualization tools
  • Undergraduate or advanced degree in analytics, data science, or statistics
  • Experience with clustering, classification, and link analysis
  • Experience working in fast-paced and rapidly changing environments
  • Experience designing and implementing product-level fraud and risk controls
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