Data Analyst

at Stripe

📍 Toronto, Canada

CAD 121,100-181,700 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

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Stripe's 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 will work with fundamental data at Stripe and use it to help drive company-wide initiatives. Stripe has a variety of Data Analytics roles and teams and will seek to align you with the most relevant team based on your background.

Responsibilities

Partner with teams across Stripe to ensure 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 in collaboration with leaders.
Build metrics, scalable data pipelines, dashboards, and reports to inform and run the business.
Deliver actionable business recommendations through analyses and data storytelling.
Design, implement, and maintain data pipelines and dashboards based on stakeholder requirements.
Collaborate with cross-functional teams to deliver strategic insights, benchmarks, and analyses that provide recommendations.
Build self-service tooling and provide training to help stakeholders become data literate and self-sufficient in autonomous reporting capabilities.

Requirements

Minimum Requirements

MS/MA plus 2 years, or BS/BA plus 3 years, of full-time experience exclusive of internships in Business Intelligence Engineering, Data Analyst, or Business Analyst roles.
Proficiency in SQL.
Proven ability to manage and deliver multiple projects with great attention to detail.
Ability to clearly communicate results and drive impact.
Experience collaborating with cross-functional teams to deliver strategic insights, benchmarks, and analyses.

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.
Good 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.