Data Scientist, Core Infrastructure
HybridSeattle, Washington, United States
Job Summary
Analyze infrastructure usage, efficiency, and workloads to predict demand and inform capacity planning. Develop models and strategies for efficient compute resource consumption and provisioning. Collaborate with engineers, engineering leadership, and finance teams to ensure data-driven infrastructure decisions that reduce costs and improve reliability. Provide actionable insights to influence technical and financial strategies within Stripe. You will act as a key strategic data partner to the Core Infrastructure organization, helping craft and drive the strategy needed to ensure Stripe scales with efficiency and dependability as the business grows. This role requires a hybrid schedule of 50% in-office time in Seattle, WA, or San Francisco, CA.
Required Qualifications
- PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience
- 3-8+ years of experience with a focus on infrastructure, cloud environments, and resource utilization/allocation
- Proficiency in SQL and a computing language such as Python or R
- Experience in analyzing logs/telemetry, scheduling optimization, or cloud infrastructure engineering
- Ability to effectively work both independently and with cross-disciplinary teams, including engineering and finance, to deliver impactful results
- A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
- Solid business acumen and experience in synthesizing complex analyses into actionable recommendations
- A track record of building relationships with and influencing the decisions of senior technical leadership
- A builder's mindset with a willingness to question assumptions and conventional wisdom
- Seattle, WA or San Francisco, CA (Hybrid: 50% in office)
Desired Qualifications
- Background in deploying data models in production environments and optimizing their performance
- Experience in using, deploying on, and analyzing usage data from public cloud providers
- Familiarity with distributed computing tools such as Spark and Hadoop
- A PhD or MS in a quantitative field like Computer Science & Engineering, Statistics, Mathematics, Operations Research, Industrial Engineering, Management Science, or related disciplines
- Strong business acumen with a track record of translating complex data analyses into actionable business recommendations
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