Role at a glance
- Salary
- Not Disclosed
- Location
- United States Seattle, United States
- Work arrangement
- Hybrid
- Employment
- Full-time
- Experience
- 3-8+ years of experience with a focus on infrastructure, cloud environments, and resource utilization/allocation.
- Education
- PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience.
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Role Summary
The Data Scientist will join Stripe’s data science team supporting core infrastructure and cloud platforms. The role partners with engineering leadership and finance to guide infrastructure strategy, capacity planning, efficiency, and dependability as Stripe scales.
What You'll Do
- 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 on data-driven infrastructure decisions.
- Provide actionable insights and recommendations to improve infrastructure operations, reduce costs, and improve reliability.
- Use analytical expertise to influence technical and financial strategies within Stripe.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Data science or quantitative modeling experience; infrastructure, cloud environments, and resource utilization/allocation; SQL and Python or R; analyzing logs/telemetry, scheduling optimization, or cloud infrastructure engineering; cross-disciplinary collaboration; project delivery; business acumen; influencing senior technical leadership.
Required
- 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
- 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
Preferred
- 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...
- Strong business acumen with a track record of translating complex data analyses into actionable business recommendations
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
You’ll be joining the data science team at Stripe responsible for our overall infrastructure, with a focus on core systems and cloud platforms. Projects include, but are not limited to:
- Developing models to predict resource needs as Stripe demand increases;
- Working closely with engineers to improve the cost and performance of platforms and services;
- Employing quantitative methods to drive and automate fleet decisions.
You will act as a key strategic data partner to the Core Infrastructure organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe can continue to scale with efficiency and dependability as our business rapidly grows.
What you'll do
As a Data Scientist, your role will involve:
- 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 Stripe makes the right, data-driven, infrastructure decisions.
- Providing actionable insights and recommendations to improve infrastructure operations to reduce costs and improve reliability.
- Utilizing your analytical expertise to influence both technical and financial strategies within Stripe.
Who you are
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Location Requirement
- Seattle, WA or San Francisco, CA (Hybrid: 50% in office)
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.
- 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.
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.
About the company
Stripe
Large Enterprise
Stripe is a leading financial technology company that provides a robust platform for online payment processing and ecommerce solutions. Founded in 2010, Stripe enables businesses of all sizes to accept payments, send payouts, and manage their online transactions seamlessly. With a focus on innovation and user experience, Stripe offers a range of APIs and tools that empower developers to integrate payment functionality quickly and efficiently. Trusted by millions of businesses worldwide, Stripe continues to shape the future of online commerce and financial services.
Stripe is a leading financial technology company that provides a robust platform for online payment processing and ecommerce solutions. Founded in 2010, Stripe enables businesses of all sizes to accept payments, send payouts, and manage their online transactions seamlessly. With a focus on innovation and user experience, Stripe offers a range of APIs and tools that empower developers to integrate payment functionality quickly and efficiently. Trusted by millions of businesses worldwide, Stripe continues to shape the future of online commerce and financial services.