Stripe is hiring a Internal Audit Data Analytics Lead in 6480 Internal Audit — Toronto, New York, San Francisco. 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.
Stripe builds the most powerful and flexible tools for running an internet business. We handle hundreds of billions of dollars each year and enable millions of users around the world to scale faster and more efficiently by building their businesses on Stripe.
About the team
Company context from the listing:
Our IA team is responsible for providing objective feedback and insights across the company in relation to the design and effectiveness of Stripe’s business processes, its compliance with laws and regulations and its risk management framework. Unique in our purpose is a cross-functional mandate that invites viewing through a wide lens and collaborating across the business.
This position can be based in Toronto, New York, or San Francisco.
What you’ll do
Day-to-day scope for the Internal Audit Data Analytics Lead as described in the posting:
Responsibilities
Day-to-day scope for the Internal Audit Data Analytics Lead as described in the posting:
- Complete data analytics as part of audit engagements in collaboration with the IA team.
- Drive the use of AI across the audit team and leverage it in audit engagements
- Participate in audit walkthroughs and develop work programs for the in scope areas
- Lead DA brainstorming sessions with the audit team to discuss best use of data analytics techniques in audit planning and fieldwork
- Assist with substantive testing of audit findings during reporting
- Document the data analytics and audit tests in work papers.
Who you are
Experience and skills the team lists as required:
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.
Minimum requirements
Experience and skills the team lists as required:
- 5-10 years of professional experience working in audit data analytics
- Expertise with SQL, schema and ETL design, and data pipeline development/maintenance (e.g., Airflow).
- Familiarity with scripting/programming for data mining and modeling (R, Python) and ETL development (Python).
- Experience with and knowledge of machine learning techniques.
- Experience with reporting and visualization platforms (e.g., Tableau).
- Exquisite attention to detail.
- A passion for building unreasonably good products and for driving defining impact.
- Versatility and willingness to learn new technologies on the job.
- High tolerance for rapid change and ability to navigate ambiguity.
- Strong communication skills with the ability to simplify and share succinctly.
- Bachelor's degree in Statistics, Computer Science, Economics, or a related quantitative field.
- Experience working with basic git command
Preferred qualifications
Experience and skills the team lists as required:
- Previous experience in a high volume transactional payment environment
- Passionate about audit and data
Build a standout application
For the Internal Audit Data Analytics Lead 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.