We’re looking for data scientists to join the Data Science team who are excited about applying their analytical skills to understand our users and influence decision making. If you are naturally data curious, excited about deriving insights from data, and motivated by having impact on the business, we want to hear from you.
You’ll be working closely with the Threat Operations team, responsible for building security analytics, curating threat intelligence, performing attack simulations and investigating, responding and providing awareness of potential security concerns. Stripe is becoming an increasingly critical piece of the world’s financial infrastructure, powering businesses all over the world. We process payments, run marketplaces, detect fraud and help entrepreneurs start an internet business from anywhere in the world. Our users trust us with some of their most sensitive information. Security is a top priority for Stripe and a first-class consideration for everything we do. We build products that are secure by default and continuously raise the bar on security.
Work cross-functionally with security experts and engineering teams across the company to develop real-time scalable solutions for monitoring and response needs.
Build statistical, machine learning and simulation models on large datasets to measure results and outcomes, detect anomalies, automatically investigate alerts, and drive programmatic actions.
Design and implement tools for monitoring and observability
Drive the collection of new data and the enrichment of existing data sources such (Network Telemetry, Host Based Telemetry, etc.)
Create analyses that tell a “story” focused on insights, not just data.
We’re looking for someone with:
6+ years experience working with 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).
Existing experience with network security and incident response
Expert knowledge of a scientific computing language (such as R or Python) and SQL.
Strong knowledge of statistics and machine learning
Ability to communicate results clearly and a focus on driving impact.
Nice to haves:
Experience designing and implementing complex modeling solutions from ideation to production at scale
Experience influencing high-impact decisions
Strong project management and organizational skills
Experience with data-distributed tools (Scalding, Spark, Hadoop, Pig, etc)