Data Analyst

Uncover; Canada; Hybrid; CAD 90,000 - 140,000; Full time

Job summary

Stripe Data Science seeks a data analytics professional to partner with product and business teams. You will develop models, data products and insights to guide decisions, and build scalable data pipelines, dashboards and reports to run the business. You will deliver actionable recommendations through analyses and data storytelling.

You should have strong SQL skills, experience in BI roles, and the ability to drive impact across cross-functional partners while communicating clearly and concisely.

Qualifications

• MS/MA + 2 years or BS/BA + 3 years of full-time experience in BI/Analytics roles.
• Proficiency in SQL and ability to design data pipelines and dashboards.
• Strong communication and ability to drive impact with analytics.

Responsibilities

• Build metrics, scalable data pipelines, dashboards and reports.
• Translate business needs into data problems and insights.
• Deliver actionable recommendations through analyses and storytelling.
• Partner with cross-functional teams to drive strategic insights.

Skills

SQL

Data analysis

Dashboard development

Communication

Project management

Data pipelines

Stakeholder engagement

Python

Education

MS/MA in a relevant field

BS/BA in a relevant field

Tools

Spark

Python

Job description

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

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. We have a variety of Data Analytics roles and teams across Stripe and will seek to align you to the most relevant team based on your background.

What you'll do

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. You'll also work with leaders to translate business needs into data problems. You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business. You'll deliver actionable business recommendations through analyses and data storytelling.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 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

• 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