Stripe is hiring a Data Analyst in 7112 Data Science — Canada. The overview below is synthesized from the employer posting on stripe.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
Who we are
About Stripe
Company context from the listing:
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.
About the team
Company context from the listing:
Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives.
What you'll do
Day-to-day scope for the Data Analyst as described in the posting:
In this role, you'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll work closely with partners to extract insights from the rich and complex data at Stripe.
Who you are
Experience and skills the team lists as required:
The listing frames the Data Analyst at Stripe as a hands-on product role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
Experience and skills the team lists as required:
- MS/MA + 2 years or BS/BA + 3 years of full-time experience exclusive of internships in Business Intelligence Engineering, Data Analyst, and Business Analyst roles
- Proficiency in SQL
- Proven ability to manage and deliver on multiple projects with great attention to detail
- Ability to clearly communicate results and drive impact
- Ability to design, implement, and maintain data pipelines and dashboards to generate actionable insights based on stakeholder requirements
- Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses that provide recommendations
- Ability to enable stakeholders and partners by building self-service tooling and providing training to empower stakeholder teams to be data literate and self-sufficient in autonomous reporting capabilities
Preferred qualifications
Experience and skills the team lists as required:
- Prior experience at a growth-stage internet or software company
- Experience with distributed data frameworks like Spark to write and debug data pipelines
- Good understanding of development processes and best practices like engineering standards, code reviews, and testing
- Strong statistical knowledge
- Working knowledge of Python
- Experience creating leadership-level reporting, such as QBRs, MBRs
- Proficiency with AI tools to accelerate model development, analysis, and coding
Build a standout application
For the Data Analyst at Stripe, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
Web3 hiring values reliability: on-time follow-through, clear writing, and a track record of improving runbooks and tooling. Treat the application as a work sample. For interviews, be ready to walk through how you prioritize across time zones, handle a difficult user, and decide when to escalate versus resolve directly. Show how you document decisions so the next teammate benefits.
In a distributed Web3 org, trust builds through written clarity. Use the cover note to demonstrate it. Add links to public work, keep formatting scannable, and close with a clear ask. Hiring managers skim — make impact obvious in the first half-page.
Career growth in Web3 rewards continuous learning. Follow protocol changelogs, practice with testnets, and contribute to open issues. Small, consistent contributions compound into credibility more than one-off credentials.