Job description
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 Security Incident Response team works to analyze, investigate, and respond to threats before they impact Stripe’s business or users. From external attacks to insider threats, our goal is to respond with speed and precision, remediate, and support the incident postmortem process. The team is distributed, working primarily in Eastern and Pacific time zones, and will regularly coordinate with stakeholders in Europe and Asia.
What you’ll do
You will leverage your security engineering experience to improve incident response capabilities at Stripe. With an emphasis on user and entity behavior analytics, as well as endpoint hardening, you will gain a deep understanding of Stripe’s systems, tooling, and workflows to be able to differentiate between legitimate and malicious activity. Using both threat intelligence and collected telemetry, you will guide and build Stripe-specific signals enrichment logic and incident response solutions that scale with our company. Lastly, your analytic capabilities will be critical during security incidents to reduce uncertainty, uncover root causes, and inform future prevention and detection mechanisms.
Responsibilities
- Work with security engineering and data science teams to build solutions for analyzing security events data at scale and protecting Stripe networks, systems, and data from threats.
- Contribute to strategic objectives, while aligning technical vision across dependent teams.
- Develop requirements for detection models and enhancements to existing systems, setting a high standard for technical decision-making influenced by industry best practices.
- Collect, transform, and ingest raw data from disparate sources into threat detection pipelines, ensuring the solutions developed reflect consistent engineering quality.
- Analyze and investigate a broad range of threats or activities occurring on client devices.
- Provide actionable insights to help identify, prevent, detect, and respond to anomalous or potentially malicious user and entity activity, fostering creative problem-solving.
- Streamline incident response capabilities, ensuring the tooling and processes are clear, while mentoring team members to improve overall incident response practices.
- Act as the subject-matter expert and primary contact for stakeholders invested in Security Analytics & Detection programs, promoting strategic alignment with broader company initiatives.
- Collaborate effectively with teammates, leading projects and championing rigorous engineering standards within the team.
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
- 7+ years experience analyzing large data sets to solve problems and/or building models with a behavioral approach to security
- B.S. or M.S. in Cybersecurity, Computer Science, or related field
- Expert knowledge of Python and SQL, and familiarity with other programming languages
- 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
- Proficiency with developing and using novel analytical methods to build, automate, and improve detection and response systems
- Ability to communicate results clearly, focus on impact, and think holistically about reducing risk in a complex environment
Preferred qualifications
- An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.
- Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)
- Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)
- Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment
- Familiarity with network observability, security software, or data engineering solutions (osquery, Splunk, etc.)
- Experience in one or more of the following areas: user and entity behavior analytics (UEBA), security information event management (SIEM), security orchestration automation and response (SOAR), or data loss prevention (DLP)
