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.
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. To further this important mission, Stripe is building a world class Internal Audit (IA) team. Our IA mission is to make the business better as it grows. We are consumed with the goal of being agile with the business, powered by technology and an accelerator to the speed of controls integration and compliance adoption.
About the team
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. To enable this engagement, we must build and scale in a rapid-growth, high-volume environment. This is a unique opportunity to join a growing Data Analytics team within audit and work on providing data driven insights across the IA lifecycle. The DA Lead will support Data Analytics and audit fieldwork in execution of the approved Global Audit Plan. They will help develop embedded audit analytics as part of audit planning, fieldwork, and reporting through the execution of data analytics test steps. The DA Lead will also help drive the usage of AI to help drive more efficient and effective audits and will be a key member of the IA team who will help us elevate the ambitions of Stripe.
This position can be based in Toronto, New York, San Francisco, Atlanta or Seattle.
What you’ll do
Responsibilities
- 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
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. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- 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
- Previous experience in a high volume transactional payment environment
- Passionate about audit and data