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About the Role
Join Stripe's data science team focused on infrastructure, core systems, and cloud platforms. You will be a key strategic data partner, helping to craft and drive the strategy and tactics for scaling Stripe with efficiency and dependability.
Responsibilities
- 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.
- Provide actionable insights and recommendations to improve infrastructure operations, reduce costs, and enhance reliability.
- Utilize analytical expertise to influence technical and financial strategies within Stripe.
- Develop models to predict resource needs as Stripe demand increases.
- Work closely with engineers to improve the cost and performance of platforms and services.
- Employ quantitative methods to drive and automate fleet decisions.
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 a 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.
- A builder's mindset with a willingness to question assumptions and conventional wisdom.
- 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.
- Strong business acumen with a track record of translating complex data analyses into actionable business recommendations.
Skills
- Data Science
- Quantitative Modeling
- Infrastructure
- Cloud Environments
- Resource Utilization/Allocation
- SQL
- Python
- R
- Log Analysis
- Telemetry Analysis
- Scheduling Optimization
- Cloud Infrastructure Engineering
- Independent Work
- Cross-disciplinary Teamwork
- Project Management
- Attention to Detail
- Business Acumen
- Complex Analysis Synthesis
- Relationship Building
- Influencing Senior Technical Leadership
- Production Data Model Deployment
- Production Data Model Optimization
- Public Cloud Usage Analysis
- Distributed Computing Tools
- Spark
- Hadoop
Location
- San Francisco, CA
- Seattle, WA
Work Type
- Full-time
Experience Level
- 3+ years (PhD)
- 6+ years (MS/MA)
- 8+ years (BS/BA)
- 3-8+ years (infrastructure focus)
Education Level
- PhD
- MS
- MA
- BS
- BA
- PhD or MS in a quantitative field like Computer Science & Engineering, Statistics, Mathematics, Operations Research, Industrial Engineering, Management Science, or related disciplines.
About the Company
- Stripe is a financial infrastructure platform for businesses.
- Millions of companies use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.
- Stripe's mission is to increase the GDP of the internet.