数据科学家，核心基础设施
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Data Scientist, Core InfrastructureStripe · Seattle
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职位描述
机器翻译我们是谁
关于 Stripe
Stripe 是一个面向企业的金融基础设施平台。数百万家公司——从全球最大的企业到最有雄心的初创公司——都在使用 Stripe 来接受付款、增长收入并加速新的商业机会。我们的使命是提升互联网的 GDP，而我们面前还有大量工作要做。这意味着你拥有一个前所未有的机会，在从事你职业生涯中最重要的工作的同时，让全球经济触手可及。
关于团队
你将加入 Stripe 的数据科学团队，负责我们的整体基础设施，重点关注核心系统和云平台。项目包括但不限于：
• 开发模型，以预测随着 Stripe 需求增长而产生的资源需求；
• 与工程师紧密合作，提升平台和服务的成本与性能；
• 运用定量方法来推动并自动化机群决策。
你将作为 Stripe 核心基础设施组织的重要战略数据合作伙伴，帮助制定、指导和推动所需的战略与战术，以帮助确保 Stripe 在我们的业务快速增长时仍能以高效和可靠的方式持续扩展。
你将做什么
作为一名数据科学家，你的职责将包括：
• 分析基础设施使用情况、效率和工作负载，以预测需求并为容量规划提供依据。
• 开发模型和策略，以实现高效的计算资源消耗和配置。
• 与工程师、工程领导层和财务团队协作
岗位职责
作为一名数据科学家，你的职责将包括：
• 分析基础设施使用情况、效率和工作负载，以预测需求并为容量规划提供依据。
• 开发模型和策略，以实现高效的计算资源消耗和配置。
• 与工程师、工程领导层和财务团队协作，确保 Stripe 做出正确的、由数据驱动的基础设施决策。
• 提供可执行的洞察和建议，以改进基础设施运营，从而降低成本并提高可靠性。
• 运用你的分析专长，影响 Stripe 内部的技术和财务战略。
任职要求
我们正在寻找符合该职位最低要求的人选。如果你符合这些要求，我们鼓励你申请。优先资格是加分项，而非必需条件。
地点要求
• 华盛顿州西雅图或加利福尼亚州旧金山（混合办公：50% 到办公室）
最低要求
• 博士学历并具有 3 年以上、硕士或文学硕士学历并具有 6 年以上，或学士或文学学士学历并具有 8 年以上数据科学或定量建模经验。 • 3-8 年以上经验，重点关注基础设施、云环境和资源利用率/分配。
• 精通 SQL 以及一种计算语言，如 Python 或 R。
• 具有分析日志/遥测数据、调度优化或云基础设施工程方面的经验。
• 能够有效地独立工作，并与跨学科团队（包括工程和财务）合作，交付有影响力的成果。
• 已证明有能力管理并交付多个项目，且高度注重细节。
• 扎实的商业敏锐度，以及将复杂分析综合为可执行建议的经验。
• 有建立关系并影响高级技术领导层决策的良好记录。
• 具备建设者的心态，愿意质疑假设和传统观念。
• 具有在生产环境中部署数据模型并优化其性能的背景。
• 具有使用、部署在公共云提供商上并分析其使用数据的经验。
• 熟悉 Spark 和 Hadoop 等分布式计算工具。
• 拥有计算机科学与工程、统计学、数学、运筹学、工业工程、管理科学或相关学科等定量领域的博士或硕士学位。
• 强大的商业敏锐度，并有将复杂数据分析转化为可执行业务建议的良好记录。
以上内容由机器翻译自动生成，可能存在错误；投递前请以雇主原文为准。
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职位描述
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.
• Collaboratin
岗位职责
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.
任职要求
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.
• 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.