# Data Scientist, Core Infrastructure

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** San Francisco, CA, Seattle, WA
**Role:** Data Science
**Experience:** 8+ years
**Skills:** SQL, Python, R, Spark, Hadoop, Data Science, Quantitative Modeling, Cloud Infrastructure, Distributed Computing
**Posted:** 2026-07-22

> Data Scientist analyzing infrastructure usage, efficiency, and workloads to predict demand, optimize compute resources, and drive data-informed capacity planning and cost reduction decisions in collaboration with engineering and finance teams. Requires advanced degree plus 3-8+ years experience in data science with infrastructure/cloud focus, SQL, Python/R, and strong business acumen.

## Job Description

## What you'll do
- Analyzing infrastructure usage, efficiency, and workloads to predict demand and inform capacity planning.
- Developing models and strategies for efficient compute resource consumption and provisioning.
- Collaborating with engineers, engineering leadership, and finance teams to ensure data-driven infrastructure decisions.
- Providing actionable insights and recommendations to improve infrastructure operations to reduce costs and improve reliability.
- Utilizing analytical expertise to influence both technical and financial strategies.

## Minimum requirements
- 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.
- Demonstrated ability to manage and deliver on multiple projects with high attention to detail.
- Solid business acumen and experience in synthesizing complex analyses into actionable recommendations.
- Track record of building relationships with and influencing the decisions of senior technical leadership.
- Builder's mindset with a willingness to question assumptions and conventional wisdom.

## Preferred 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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