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

Our mission is to deliver insightful analyses and durable data products
to anticipate and inform the right decisions at the right time about
Stripe's cloud, security and tech enablement infrastructures.

What you’ll do

You will work with our Security Analytics and Detection team, which is
committed to promoting data security and protecting Stripe from internal
and external threats to its assets and infrastructure.  We’re looking
for talented candidates who can leverage data science to build out
security capabilities with an emphasis on application security and
vulnerability management. Your work will be critical to reducing risks
and promoting trust and integrity within Stripe.

Responsibilities 

• Research, develop, design, and build models for threat detection,
  guiding processes for signal ingestion, data analytics, and automation
  to improve detection and investigation of potentially malicious
  activity;
  
• Work cross-functionally with data science, software development, and
  security engineering teams to architect solutions for analyzing
  security events data at scale and protecting Stripe networks, systems,
  and data from external threats;
  
• Build statistical, machine learning, and simulation models on large
  datasets, including unstructured data from disparate sources;
  
• Drive the creation, collection and processing of new data and the
  enrichment of existing data sources (e.g., log data, network,
  host-based telemetry, etc.);
  
• Develop technical and functional requirements to deploy novel
  detection and vulnerability identification capabilities that mitigate
  emergent and current threats;
  
• Provide actionable insights to stakeholders to help identify, prevent,
  and detect anomalous usage of Stripe’s endpoints;
  
• Act as a force multiplier for quantitative methods in our Security
  organization and help train and mentor engineers on statistical
  techniques.
  

Who you are

We’re looking for a data scientist with security experience who is
excited about applying their analytical skills to develop methods,
systems and processes to protect Stripe from external threats and
vulnerabilities. If you are naturally data curious, enjoy deriving
insights from data, and motivated by the opportunity to build
engineering solutions from the ground up that significantly impact the
business, we want to hear from you!

Minimum requirements

• 5+ years experience working with security-related information and
  analyzing large data sets to solve problems.
  
• A PhD or MS in a quantitative field (e.g., Applied Mathematics,
  Computer Science, Statistics, Engineering, Natural Sciences).
  
• A proven track record of translating large and ambiguous business
  problems in mathematical models and developing data scientific
  solutions.
  
• Existing experience with network security, digital forensics, and
  incident response.
  
• Expert knowledge of Python and SQL, and familiarity with other
  programming languages (R, Go, Scala).
  
• Proficiency with popular open-source machine learning frameworks
  (scikit-learn, MLlib, pytorch, tensorflow, xgboost, etc.).
  
• Strong knowledge of statistics and machine learning.
  
• Ability to communicate results clearly and focus on impact.
  
• Ability to think creatively and holistically about reducing risk in a
  complex environment.
  
• Experience developing foundational and diverse data sources, and
  generating metrics to measure service and program effectiveness.
  
• Passion for mentoring others and building a data science and security
  community.
  

Preferred qualifications

• Experience influencing high-impact decisions.
  
• Strong project management and organizational skills.
  
• Proficiency in taking data-driven approaches to detection, building
  and automating solutions rather than relying on third party
  off-the-shelf products.
  
• Experience with data-distributed tools (Scalding, Spark, Hadoop,
  DataBricks, dbt, etc.).
  
• An adversarial mindset, understanding the goals, behaviors, and TTPs
  of threat actors.
  
• Familiarity with network observability or security software (Uptycs,
  Icebrg, Splunk, etc.).
  
• Knowledge of network protocols (DNS or HTTPS) and understanding of
  cloud computing services/deployment architecture.
  
• Working knowledge of complex distributed machine learning systems
  deployed at scale in a cloud computing environment.
  
• Experience in one or more of the following areas: security information
  event management (SIEM), enterprise risk management (ERM), common
  weakness enumeration (CWE), and/or fraud detection.