Data Analyst, SF

at Stripe

📍 South San Francisco, United States

USD 134,000-201,000 per year

MIDDLE

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 5 BI Data Pipelines @ 3 Data Science Leadership @ 3 Payments Python @ 3 Reporting @ 3 SQL @ 5 Spark @ 3

Details

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. Its mission is to increase the GDP of the internet.

About the Team

Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with fundamental data at Stripe and use it to help drive company-wide initiatives.

Responsibilities

Partner with teams across Stripe to ensure that users, products, and the business have the models, data products, and insights needed to make decisions and grow responsibly.
Extract insights from rich and complex data.
Translate business needs into data problems.
Build metrics, scalable data pipelines, dashboards, and reports to inform and run the business.
Deliver actionable business recommendations through analyses and data storytelling.
Build self-service tooling and provide training to help stakeholders become data literate and self-sufficient in autonomous reporting capabilities.

Requirements

MS or MA plus 2 years, or BS or BA plus 3 years, of full-time experience, excluding internships, in Business Intelligence Engineering, Data Analyst, or Business Analyst roles.
Proficiency in SQL.
Proven ability to manage and deliver multiple projects with strong attention to detail.
Ability to clearly communicate results and drive impact.
Ability to design, implement, and maintain data pipelines and dashboards that generate actionable insights based on stakeholder requirements.
Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses with recommendations.

Preferred Qualifications

Prior experience at a growth-stage internet or software company.
Experience with distributed data frameworks such as Spark to write and debug data pipelines.
Understanding of development processes and best practices, including engineering standards, code reviews, and testing.
Strong statistical knowledge.
Working knowledge of Python.
Experience creating leadership-level reporting, such as QBRs and MBRs.
Proficiency with AI tools to accelerate model development, analysis, and coding.