# Data Scientist, Core Infrastructure

**Company**: Stripe
**Location**: San Francisco
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Finance

**Apply**: https://job-boards.greenhouse.io/stripe/jobs/8080614?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_11c061b4-23d

## Description

## Job Description

You'll be joining the data science team at Stripe responsible for our overall infrastructure, with a focus on core systems and cloud platforms.

## Responsibilities

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.

## 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.

## Skills

### Required
- SQL
- Python
- R
- data science
- quantitative modeling
- infrastructure
- cloud environments
- resource utilization/allocation
- logs/telemetry analysis
- scheduling optimization
- cloud infrastructure engineering

### Nice to have
- deploying data models in production environments
- optimizing performance
- public cloud providers
- distributed computing tools like Spark and Hadoop
- quantitative fields like Computer Science & Engineering, Statistics, Mathematics, Operations Research, Industrial Engineering, Management Science

---

Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/stripe/jobs/8080614?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)