{
"endpoint": "ats-jobs",
"count": 1,
"truncated": true,
"took_ms": 5653,
"items": [
{
"ats": "greenhouse",
"companySlug": "stripe",
"companyName": "Stripe",
"jobId": "8172508",
"title": "Abuse Investigator",
"department": "8611 Security Analytics",
"location": "Dublin",
"locations": [
"Dublin",
"Ireland Locations"
],
"isRemote": false,
"postedAt": "2026-09-03T17:32:53.000Z",
"updatedAt": "2026-10-29T14:42:09.000Z",
"jobUrl": "https://stripe.com/jobs/search?gh_jid=8172508",
"applyUrl": "https://stripe.com/jobs/search?gh_jid=8172508",
"descriptionText": "Who we are\n\nAbout Stripe\n\nStripe 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.\n\nAbout the team\n\nAbuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve technical incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world.\n\nWhat you’ll do\n\nYou'll play a critical role in safeguarding our financial ecosystem by investigating high-risk accounts and identifying complex patterns of fraud during incidents. You will lead incident response for product abuse and fraud events, conducting deep-dive analyses to identify root causes. By collaborating cross-functionally, you will drive improvements that enhance our fraud detection and prevention strategies at scale. Your expertise will be essential in automating response processes through agentic approaches, allowing us to safeguard merchants and neutralize threats with speed and precision.\n\nResponsibilities\n\n• Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped detection and signals enrichment to reduce uncertainty and accelerate response.\n\n• As part of incidents, analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors, classifying them using FT3 (Fraud Taxonomy 3.0) to standardize threat intelligence.\n\n• Lead incident root cause analyses to identify gaps in current systems and strategies, leveraging the FT3 framework, data-driven model to drive enhancements and process improvements for emerging fraud risks.\n\n• Streamline incident response capabilities, ensuring the tooling and processes are clear, accurate and efficient\n\n• Work cross-functionally with security, fraud and data science teams to build agentic solutions for responding to abuse incidents at scale\n\n• Effectively communicate cross-functionally with legal and policy teams to assess and mitigate risks, while demonstrating strong problem-solving under pressure.\n\n• Collaborate effectively with teammates, leading projects, mentoring others, and developing and championing quality standards within the team\n\nWho you are\n\nWe'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.\n\nMinimum requirements\n\n• 3+ years of experience conducting incident response in security, product abuse or trust domains\n\n• 3+ years experience analyzing large data sets to solve problems and/or building models with a behavioral approach to fraud detection\n\n• B.S. or M.S. Computer Science or related field, or equivalent experience\n\n• Expert knowledge of Python and SQL, and familiarity with other programming languages\n\n• Existing experience with log analysis (e.g. first or third party applications, system / data access, event logs), network security, digital forensics, and incident response investigations\n\n• Ability to communicate results clearly and focus on impact\n\n• Ability to think creatively and holistically about reducing risk in a complex environment\n\nPreferred qualifications\n\n• An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.\n\n• Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)\n\n• Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)\n\n• Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment\n\n• Ability to proactively challenge the status quo by leveraging data and taking a user-centric approach to address complex product integrity challenges",
"companyInput": "stripe",
"scrapedAt": "2026-11-11T16:07:12.668Z"
}
]
}
curl --location --request GET 'https://zylalabs.com/api/14933/applicant+tracking+system+jobs+api/39020/get+company+ats+job+postings?companies=stripe&postedWithinDays=OptionalremoteOnly=false&limit=2' --header 'Authorization: Bearer YOUR_API_KEY'
注册后,每个开发者都会被分配一个个人 API 访问密钥,这是一个唯一的字母和数字组合,用于访问我们的 API 端点。要使用 申请者追踪系统职位 API 进行身份验证,只需在 Authorization 标头中包含您的 bearer token。
| 标头 | 描述 |
|---|---|
授权
|
必需
应为 Bearer access_key. 订阅后,请查看上方的"您的 API 访问密钥"。
|
来自指定公司申请人跟踪系统的实时职位发布,作为结构化的JSON
每个响应都是一个JSON,包含一个计数,一个took_ms字段和一个准备好存储或查询的平面记录数组
不 请求在服务器端处理 你只需发送你的API密钥和此端点中描述的参数
每次调用都会实时读取源,因此记录反映了请求时上游源的状态
您会收到明确的错误状态,而不是空结果,因此失败绝不会被误认为没有数据
是的,每个端点限制每个请求的记录数量;最大值在限制参数中说明
此端点返回指定公司的实时职位发布,包括职位名称、地点、远程状态、雇佣类型、发布日期和部门等详细信息
关键字段包括`jobId`、`title`、`department`、`location`、`isRemote`、`postedAt`、`jobUrl`和`applyUrl`,提供关于每个职位发布的基本信息
响应被结构化为一个 JSON 对象,包含 `count`、`took_ms` 和一个 `items` 数组,每个项目代表一个职位发布,具有详细的属性
该端点提供每个职位列表的职位名称、地点、远程工作选项、雇用类型、发布日期和部门隶属关系的信息
用户可以通过指定参数,如公司名称或职位名称,来自定义请求,以根据他们的需求过滤结果
例如 `isRemote` 表示该工作是否可以远程进行,而 `postedAt` 显示工作发布的时间,帮助用户评估工作的新鲜程度
典型的用例包括招聘网站的职位聚合 招聘分析和市场调研以了解特定行业或地点的招聘趋势
通过直接从公司的申请者跟踪系统读取数据来保持数据的准确性,确保信息反映最新的职位发布